Showing 113 of total 113 results (show query)
spedygiorgio
lifecontingencies:Financial and Actuarial Mathematics for Life Contingencies
Classes and methods that allow the user to manage life table, actuarial tables (also multiple decrements tables). Moreover, functions to easily perform demographic, financial and actuarial mathematics on life contingencies insurances calculations are contained therein. See Spedicato (2013) <doi:10.18637/jss.v055.i10>.
Maintained by Giorgio Alfredo Spedicato. Last updated 6 months ago.
actuarialfinanciallife-contingencieslife-insurancecpp
24.9 match 62 stars 7.09 score 156 scriptsjoaquinauza
DetLifeInsurance:Life Insurance Premium and Reserves Valuation
Methods for valuation of life insurance premiums and reserves (including variable-benefit and fractional coverage) based on "Actuarial Mathematics" by Bowers, H.U. Gerber, J.C. Hickman, D.A. Jones and C.J. Nesbitt (1997, ISBN: 978-0938959465), "Actuarial Mathematics for Life Contingent Risks" by Dickson, David C. M., Hardy, Mary R. and Waters, Howard R (2009) <doi:10.1017/CBO9780511800146> and "Life Contingencies" by Jordan, C. W (1952) <doi:10.1017/S002026810005410X>. It also contains functions for equivalent interest and discount rate calculation, present and future values of annuities, and loan amortization schedule.
Maintained by Joaquin Auza. Last updated 5 years ago.
actuarialactuarial-sciencelife-insurance
31.3 match 10 stars 4.70 score 3 scriptsjulianfaraway
faraway:Datasets and Functions for Books by Julian Faraway
Books are "Linear Models with R" published 1st Ed. August 2004, 2nd Ed. July 2014, 3rd Ed. February 2025 by CRC press, ISBN 9781439887332, and "Extending the Linear Model with R" published by CRC press in 1st Ed. December 2005 and 2nd Ed. March 2016, ISBN 9781584884248 and "Practical Regression and ANOVA in R" contributed documentation on CRAN (now very dated).
Maintained by Julian Faraway. Last updated 1 months ago.
15.4 match 29 stars 9.43 score 1.7k scripts 1 dependentskainhofer
LifeInsureR:Modelling Traditional Life Insurance Contracts
R6 classes to model traditional life insurance contracts like annuities, whole life insurances or endowments. Such life insurance contracts provide a guaranteed interest and are not directly linked to the performance of a particular investment vehicle, but they typically provide (discretionary) profit participation. This package provides a framework to model such contracts in a very generic (cash-flow-based) way and includes modelling profit participation schemes, dynamic increases or more general contract layers, as well as contract changes (like sum increases or premium waivers). All relevant quantities like premium decomposition, reserves and benefits over the whole contract period are calculated and potentially exported to 'Excel'. Mortality rates are given using the 'MortalityTables' package.
Maintained by Reinhold Kainhofer. Last updated 1 years ago.
29.6 match 2 stars 3.48 score 9 scripts 1 dependentskjhealy
gssrdoc:Document General Social Survey Variable
The General Social Survey (GSS) is a long-running, mostly annual survey of US households. It is administered by the National Opinion Research Center (NORC). This package contains the a tibble with information on the survey variables, together with every variable documented as an R help page. For more information on the GSS see \url{http://gss.norc.org}.
Maintained by Kieran Healy. Last updated 11 months ago.
44.9 match 2.28 score 38 scriptssleire
etrm:Energy Trading and Risk Management
Provides a collection of functions to perform core tasks within Energy Trading and Risk Management (ETRM). Calculation of maximum smoothness forward price curves for electricity and natural gas contracts with flow delivery, as presented in F. E. Benth, S. Koekebakker, and F. Ollmar (2007) <doi:10.3905/jod.2007.694791> and F. E. Benth, J. S. Benth, and S. Koekebakker (2008) <doi:10.1142/6811>. Portfolio insurance trading strategies for price risk management in the forward market, see F. Black (1976) <doi:10.1016/0304-405X(76)90024-6>, T. Bjork (2009) <https://EconPapers.repec.org/RePEc:oxp:obooks:9780199574742>, F. Black and R. W. Jones (1987) <doi:10.3905/jpm.1987.409131> and H. E. Leland (1980) <http://www.jstor.org/stable/2327419>.
Maintained by Anders D. Sleire. Last updated 2 years ago.
commoditiesenergy-tradingrisk-managementtrading-strategies
17.7 match 33 stars 5.52 score 10 scriptsmharinga
insurancerating:Analytic Insurance Rating Techniques
Functions to build, evaluate, and visualize insurance rating models. It simplifies the process of modeling premiums, and allows to analyze insurance risk factors effectively. The package employs a data-driven strategy for constructing insurance tariff classes, drawing on the work of Antonio and Valdez (2012) <doi:10.1007/s10182-011-0152-7>.
Maintained by Martin Haringa. Last updated 5 months ago.
actuarialactuarial-scienceinsurancepricing
15.9 match 70 stars 5.89 score 28 scriptsmharinga
spatialrisk:Calculating Spatial Risk
Methods for spatial risk calculations. It offers an efficient approach to determine the sum of all observations within a circle of a certain radius. This might be beneficial for insurers who are required (by a recent European Commission regulation) to determine the maximum value of insured fire risk policies of all buildings that are partly or fully located within a circle of a radius of 200m. See Church (1974) <doi:10.1007/BF01942293> for a description of the problem.
Maintained by Martin Haringa. Last updated 7 months ago.
actuarial-scienceinsurancesolvency-iispatialcpp
14.3 match 19 stars 5.06 score 30 scriptspaul-buerkner
brms:Bayesian Regression Models using 'Stan'
Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include both theory-driven and data-driven non-linear terms, auto-correlation structures, censoring and truncation, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their prior knowledge. Models can easily be evaluated and compared using several methods assessing posterior or prior predictions. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>; Bürkner (2018) <doi:10.32614/RJ-2018-017>; Bürkner (2021) <doi:10.18637/jss.v100.i05>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
Maintained by Paul-Christian Bürkner. Last updated 3 days ago.
bayesian-inferencebrmsmultilevel-modelsstanstatistical-models
3.8 match 1.3k stars 16.61 score 13k scripts 34 dependentsmages
ChainLadder:Statistical Methods and Models for Claims Reserving in General Insurance
Various statistical methods and models which are typically used for the estimation of outstanding claims reserves in general insurance, including those to estimate the claims development result as required under Solvency II.
Maintained by Markus Gesmann. Last updated 1 months ago.
6.0 match 82 stars 10.04 score 196 scripts 2 dependentsjimbrig
lossrx:Actuarial Loss Development and Reserving with R
Actuarial Loss Development and Reserving Helper Functions and ShinyApp.
Maintained by Jimmy Briggs. Last updated 3 months ago.
actuarial-scienceclaims-dataclaims-reservingdata-scienceinsurancemodellingproperty-casualtyreservingrshinyworkflow
10.0 match 14 stars 5.89 score 7 scriptsgpitt71
clmplus:Tool-Box of Chain Ladder Plus Models
Implementation of the age-period-cohort models for the claim development presented in the manuscript 'Replicating and extending chain-ladder via an age-period-cohort structure on the claim development in a run-off triangle' <doi:10.48550/arXiv.2301.03858>.
Maintained by Gabriele Pittarello. Last updated 5 months ago.
age-period-cohort-modelsinsurancenon-lifereserving
10.0 match 4 stars 5.30 score 8 scriptssbgraves237
Ecdat:Data Sets for Econometrics
Data sets for econometrics, including political science.
Maintained by Spencer Graves. Last updated 4 months ago.
6.8 match 2 stars 7.25 score 740 scripts 3 dependentsalexkz
kernlab:Kernel-Based Machine Learning Lab
Kernel-based machine learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods 'kernlab' includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes and a QP solver.
Maintained by Alexandros Karatzoglou. Last updated 7 months ago.
4.0 match 21 stars 12.26 score 7.8k scripts 487 dependentstreynkens
ReIns:Functions from "Reinsurance: Actuarial and Statistical Aspects"
Functions from the book "Reinsurance: Actuarial and Statistical Aspects" (2017) by Hansjoerg Albrecher, Jan Beirlant and Jef Teugels <https://www.wiley.com/en-us/Reinsurance%3A+Actuarial+and+Statistical+Aspects-p-9780470772683>.
Maintained by Tom Reynkens. Last updated 4 months ago.
extremesreinsurancerisk-analysiscpp
7.2 match 22 stars 6.31 score 186 scriptsr-forge
copula:Multivariate Dependence with Copulas
Classes (S4) of commonly used elliptical, Archimedean, extreme-value and other copula families, as well as their rotations, mixtures and asymmetrizations. Nested Archimedean copulas, related tools and special functions. Methods for density, distribution, random number generation, bivariate dependence measures, Rosenblatt transform, Kendall distribution function, perspective and contour plots. Fitting of copula models with potentially partly fixed parameters, including standard errors. Serial independence tests, copula specification tests (independence, exchangeability, radial symmetry, extreme-value dependence, goodness-of-fit) and model selection based on cross-validation. Empirical copula, smoothed versions, and non-parametric estimators of the Pickands dependence function.
Maintained by Martin Maechler. Last updated 11 days ago.
3.8 match 11.83 score 1.2k scripts 86 dependentsmstasinopoulos
gamlss.data:Data for Generalised Additive Models for Location Scale and Shape
Data used as examples in the current two books on Generalised Additive Models for Location Scale and Shape introduced by Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>.
Maintained by Mikis Stasinopoulos. Last updated 1 years ago.
5.6 match 7.04 score 108 scripts 49 dependentscran
MASS:Support Functions and Datasets for Venables and Ripley's MASS
Functions and datasets to support Venables and Ripley, "Modern Applied Statistics with S" (4th edition, 2002).
Maintained by Brian Ripley. Last updated 16 days ago.
3.8 match 19 stars 10.53 score 11k dependentsr-forge
Sleuth3:Data Sets from Ramsey and Schafer's "Statistical Sleuth (3rd Ed)"
Data sets from Ramsey, F.L. and Schafer, D.W. (2013), "The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed)", Cengage Learning.
Maintained by Berwin A Turlach. Last updated 1 years ago.
6.0 match 6.38 score 522 scriptsvigou3
actuar:Actuarial Functions and Heavy Tailed Distributions
Functions and data sets for actuarial science: modeling of loss distributions; risk theory and ruin theory; simulation of compound models, discrete mixtures and compound hierarchical models; credibility theory. Support for many additional probability distributions to model insurance loss size and frequency: 23 continuous heavy tailed distributions; the Poisson-inverse Gaussian discrete distribution; zero-truncated and zero-modified extensions of the standard discrete distributions. Support for phase-type distributions commonly used to compute ruin probabilities. Main reference: <doi:10.18637/jss.v025.i07>. Implementation of the Feller-Pareto family of distributions: <doi:10.18637/jss.v103.i06>.
Maintained by Vincent Goulet. Last updated 2 months ago.
3.8 match 12 stars 9.44 score 732 scripts 35 dependentsr-forge
Sleuth2:Data Sets from Ramsey and Schafer's "Statistical Sleuth (2nd Ed)"
Data sets from Ramsey, F.L. and Schafer, D.W. (2002), "The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed)", Duxbury.
Maintained by Berwin A Turlach. Last updated 1 years ago.
6.0 match 5.70 score 191 scriptsrobjhyndman
fpp2:Data for "Forecasting: Principles and Practice" (2nd Edition)
All data sets required for the examples and exercises in the book "Forecasting: principles and practice" (2nd ed, 2018) by Rob J Hyndman and George Athanasopoulos <https://otexts.com/fpp2/>. All packages required to run the examples are also loaded.
Maintained by Rob Hyndman. Last updated 2 years ago.
3.8 match 106 stars 8.57 score 1.8k scripts 1 dependentsrobjhyndman
fpp3:Data for "Forecasting: Principles and Practice" (3rd Edition)
All data sets required for the examples and exercises in the book "Forecasting: principles and practice" by Rob J Hyndman and George Athanasopoulos <https://OTexts.com/fpp3/>. All packages required to run the examples are also loaded. Additional data sets not used in the book are also included.
Maintained by Rob Hyndman. Last updated 6 months ago.
3.8 match 142 stars 8.47 score 2.5k scriptsalanarnholt
BSDA:Basic Statistics and Data Analysis
Data sets for book "Basic Statistics and Data Analysis" by Larry J. Kitchens.
Maintained by Alan T. Arnholt. Last updated 2 years ago.
3.4 match 7 stars 9.11 score 1.3k scripts 6 dependentskainhofer
MortalityTables:A Framework for Various Types of Mortality / Life Tables
Classes to implement, analyze and plot cohort life tables for actuarial calculations. Birth-year dependent cohort mortality tables using a yearly trend to extrapolate from a base year are implemented, as well as period life table, cohort life tables using an age shift, and merged life tables. Additionally, several data sets from various countries are included to provide widely-used tables out of the box.
Maintained by Reinhold Kainhofer. Last updated 1 years ago.
5.3 match 1 stars 5.70 score 84 scripts 2 dependentstrevorhastie
ISLR:Data for an Introduction to Statistical Learning with Applications in R
We provide the collection of data-sets used in the book 'An Introduction to Statistical Learning with Applications in R'.
Maintained by Trevor Hastie. Last updated 4 years ago.
3.8 match 4 stars 7.58 score 10k scripts 2 dependentsnickch-k
causaldata:Example Data Sets for Causal Inference Textbooks
Example data sets to run the example problems from causal inference textbooks. Currently, contains data sets for Huntington-Klein, Nick (2021) "The Effect" <https://theeffectbook.net>, first and second edition, Cunningham, Scott (2021, ISBN-13: 978-0-300-25168-5) "Causal Inference: The Mixtape", and Hernán, Miguel and James Robins (2020) "Causal Inference: What If" <https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/>.
Maintained by Nick Huntington-Klein. Last updated 4 months ago.
3.6 match 136 stars 7.43 score 144 scripts 1 dependentscran
insuranceData:A Collection of Insurance Datasets Useful in Risk Classification in Non-life Insurance.
Insurance datasets, which are often used in claims severity and claims frequency modelling. It helps testing new regression models in those problems, such as GLM, GLMM, HGLM, non-linear mixed models etc. Most of the data sets are applied in the project "Mixed models in ratemaking" supported by grant NN 111461540 from Polish National Science Center.
Maintained by Alicja Wolny--Dominiak. Last updated 11 years ago.
17.6 match 2 stars 1.42 scorepeterkdunn
GLMsData:Generalized Linear Model Data Sets
Data sets from the book Generalized Linear Models with Examples in R by Dunn and Smyth.
Maintained by Peter K. Dunn. Last updated 3 years ago.
9.1 match 2.61 score 220 scriptsagi-lab
SynthETIC:Synthetic Experience Tracking Insurance Claims
Creation of an individual claims simulator which generates various features of non-life insurance claims. An initial set of test parameters, designed to mirror the experience of an Auto Liability portfolio, were set up and applied by default to generate a realistic test data set of individual claims (see vignette). The simulated data set then allows practitioners to back-test the validity of various reserving models and to prove and/or disprove certain actuarial assumptions made in claims modelling. The distributional assumptions used to generate this data set can be easily modified by users to match their experiences. Reference: Avanzi B, Taylor G, Wang M, Wong B (2020) "SynthETIC: an individual insurance claim simulator with feature control" <arXiv:2008.05693>.
Maintained by Melantha Wang. Last updated 1 years ago.
3.8 match 12 stars 6.22 score 23 scripts 2 dependentscran
erer:Empirical Research in Economics with R
Several functions, datasets, and sample codes related to empirical research in economics are included. They cover the marginal effects for binary or ordered choice models, static and dynamic Almost Ideal Demand System (AIDS) models, and a typical event analysis in finance.
Maintained by Changyou Sun. Last updated 6 months ago.
6.9 match 3 stars 3.34 score 211 scripts 1 dependentsarne-henningsen
sampleSelection:Sample Selection Models
Two-step and maximum likelihood estimation of Heckman-type sample selection models: standard sample selection models (Tobit-2), endogenous switching regression models (Tobit-5), sample selection models with binary dependent outcome variable, interval regression with sample selection (only ML estimation), and endogenous treatment effects models. These methods are described in the three vignettes that are included in this package and in econometric textbooks such as Greene (2011, Econometric Analysis, 7th edition, Pearson).
Maintained by Arne Henningsen. Last updated 4 years ago.
3.8 match 6.10 score 311 scripts 5 dependentsfriendly
nestedLogit:Nested Dichotomy Logistic Regression Models
Provides functions for specifying and fitting nested dichotomy logistic regression models for a multi-category response and methods for summarising and plotting those models. Nested dichotomies are statistically independent, and hence provide an additive decomposition of tests for the overall 'polytomous' response. When the dichotomies make sense substantively, this method can be a simpler alternative to the standard 'multinomial' logistic model which compares response categories to a reference level. See: J. Fox (2016), "Applied Regression Analysis and Generalized Linear Models", 3rd Ed., ISBN 1452205663.
Maintained by Michael Friendly. Last updated 10 months ago.
logistic-regressionmultinomial-logistic-regressionpolytomous-variables
3.8 match 10 stars 6.04 score 33 scriptsbpfaff
evir:Extreme Values in R
Functions for extreme value theory, which may be divided into the following groups; exploratory data analysis, block maxima, peaks over thresholds (univariate and bivariate), point processes, gev/gpd distributions.
Maintained by Bernhard Pfaff. Last updated 8 years ago.
3.8 match 2 stars 5.89 score 211 scripts 6 dependentsgavinrozzi
njtr1:Download, Analyze & Clean New Jersey Car Crash Data
Download and analyze motor vehicle crash data released by the New Jersey Department of Transportation (NJDOT). The data in this package is collected through the filing of NJTR-1 form by police officers, which provide a standardized way of documenting a motor vehicle crash that occurred in New Jersey. 3 different data tables containing data on crashes, vehicles & pedestrians released from 2001 to the present can be downloaded & cleaned using this package.
Maintained by Gavin Rozzi. Last updated 1 years ago.
njtr1new-jerseyroad-safetycar-crashescar-accidentsdata
4.8 match 5 stars 4.40 score 7 scriptsalanarnholt
PASWR:Probability and Statistics with R
Functions and data sets for the text Probability and Statistics with R.
Maintained by Alan T. Arnholt. Last updated 3 years ago.
4.5 match 2 stars 4.70 score 241 scriptssvmiller
stevedata:Steve's Toy Data for Teaching About a Variety of Methodological, Social, and Political Topics
This is a collection of various kinds of data with broad uses for teaching. My students, and academics like me who teach the same topics I teach, should find this useful if their teaching workflow is also built around the R programming language. The applications are multiple but mostly cluster on topics of statistical methodology, international relations, and political economy.
Maintained by Steve Miller. Last updated 4 days ago.
3.5 match 8 stars 5.97 score 178 scriptstrevorhastie
ISLR2:Introduction to Statistical Learning, Second Edition
We provide the collection of data-sets used in the book 'An Introduction to Statistical Learning with Applications in R, Second Edition'. These include many data-sets that we used in the first edition (some with minor changes), and some new datasets.
Maintained by Trevor Hastie. Last updated 2 years ago.
3.8 match 2 stars 5.49 score 2.2k scriptshanmingwu1103
dataSDA:Data Sets for Symbolic Data Analysis
Collects a diverse range of symbolic data and offers a comprehensive set of functions that facilitate the conversion of traditional data into the symbolic data format.
Maintained by Han-Ming Wu. Last updated 2 years ago.
7.6 match 2.70 score 2 scriptscasact
imaginator:Simulate General Insurance Policies and Losses
Simulate general insurance policies, losses and loss emergence. The package contemplates deterministic and stochastic policy retention and growth scenarios. Retention and growth rates are percentages relative to the expiring portfolio. Claims are simulated for each policy. This is accomplished either be assuming a frequency distribution per development lag or by generating random wait times until claim emergence and settlement. Loss simulation uses standard loss distributions for claim amounts.
Maintained by Brian Fannin. Last updated 3 years ago.
3.5 match 14 stars 5.51 score 23 scriptsimranshakoor
DDPM:Data Sets for Discrete Probability Models
A wide collection of univariate discrete data sets from various applied domains related to distribution theory. The functions allow quick, easy, and efficient access to 100 univariate discrete data sets. The data are related to different applied domains, including medical, reliability analysis, engineering, manufacturing, occupational safety, geological sciences, terrorism, psychology, agriculture, environmental sciences, road traffic accidents, demography, actuarial science, law, and justice. The documentation, along with associated references for further details and uses, is presented.
Maintained by Muhammad Imran. Last updated 2 years ago.
19.2 match 1.00 scorealanarnholt
PASWR2:Probability and Statistics with R, Second Edition
Functions and data sets for the text Probability and Statistics with R, Second Edition.
Maintained by Alan T. Arnholt. Last updated 3 years ago.
4.5 match 1 stars 4.24 score 260 scriptscran
BayesGOF:Bayesian Modeling via Frequentist Goodness-of-Fit
A Bayesian data modeling scheme that performs four interconnected tasks: (i) characterizes the uncertainty of the elicited parametric prior; (ii) provides exploratory diagnostic for checking prior-data conflict; (iii) computes the final statistical prior density estimate; and (iv) executes macro- and micro-inference. Primary reference is Mukhopadhyay, S. and Fletcher, D. 2018 paper "Generalized Empirical Bayes via Frequentist Goodness of Fit" (<https://www.nature.com/articles/s41598-018-28130-5 >).
Maintained by Doug Fletcher. Last updated 6 years ago.
7.5 match 2.48 score 1 dependentslightbluetitan
crimedatasets:A Comprehensive Collection of Crime-Related Datasets
A comprehensive collection of datasets exclusively focused on crimes, criminal activities, and related topics. This package serves as a valuable resource for researchers, analysts, and students interested in crime analysis, criminology, social and economic studies related to criminal behavior. Datasets span global and local contexts, with a mix of tabular and spatial data.
Maintained by Renzo Caceres Rossi. Last updated 3 months ago.
3.8 match 8 stars 4.90 score 3 scriptsenricoschumann
NMOF:Numerical Methods and Optimization in Finance
Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). The package provides implementations of optimisation heuristics (Differential Evolution, Genetic Algorithms, Particle Swarm Optimisation, Simulated Annealing and Threshold Accepting), and other optimisation tools, such as grid search and greedy search. There are also functions for the valuation of financial instruments such as bonds and options, for portfolio selection and functions that help with stochastic simulations.
Maintained by Enrico Schumann. Last updated 30 days ago.
black-scholesdifferential-evolutiongenetic-algorithmgrid-searchheuristicsimplied-volatilitylocal-searchoptimizationparticle-swarm-optimizationsimulated-annealingthreshold-accepting
1.9 match 36 stars 9.56 score 101 scripts 4 dependentskosukeimai
experiment:R Package for Designing and Analyzing Randomized Experiments
Provides various statistical methods for designing and analyzing randomized experiments. One functionality of the package is the implementation of randomized-block and matched-pair designs based on possibly multivariate pre-treatment covariates. The package also provides the tools to analyze various randomized experiments including cluster randomized experiments, two-stage randomized experiments, randomized experiments with noncompliance, and randomized experiments with missing data.
Maintained by Kosuke Imai. Last updated 3 years ago.
3.4 match 14 stars 5.29 score 23 scriptsstatmanrobin
Stat2Data:Datasets for Stat2
Datasets for the textbook Stat2: Modeling with Regression and ANOVA (second edition). The package also includes data for the first edition, Stat2: Building Models for a World of Data and a few functions for plotting diagnostics.
Maintained by Robin Lock. Last updated 6 years ago.
3.6 match 5 stars 4.94 score 544 scriptsovgu-sh
desk:Didactic Econometrics Starter Kit
Written to help undergraduate as well as graduate students to get started with R for basic econometrics without the need to import specific functions and datasets from many different sources. Primarily, the package is meant to accompany the German textbook Auer, L.v., Hoffmann, S., Kranz, T. (2024, ISBN: 978-3-662-68263-0) from which the exercises cover all the topics from the textbook Auer, L.v. (2023, ISBN: 978-3-658-42699-6).
Maintained by Soenke Hoffmann. Last updated 11 months ago.
4.0 match 4.30 score 10 scriptsspedygiorgio
markovchain:Easy Handling Discrete Time Markov Chains
Functions and S4 methods to create and manage discrete time Markov chains more easily. In addition functions to perform statistical (fitting and drawing random variates) and probabilistic (analysis of their structural proprieties) analysis are provided. See Spedicato (2017) <doi:10.32614/RJ-2017-036>. Some functions for continuous times Markov chains depend on the suggested ctmcd package.
Maintained by Giorgio Alfredo Spedicato. Last updated 4 months ago.
ctmcdtmcmarkov-chainmarkov-modelr-programmingrcppopenblascpp
1.3 match 104 stars 12.78 score 712 scripts 4 dependentssteffenmoritz
imputeR:A General Multivariate Imputation Framework
Multivariate Expectation-Maximization (EM) based imputation framework that offers several different algorithms. These include regularisation methods like Lasso and Ridge regression, tree-based models and dimensionality reduction methods like PCA and PLS.
Maintained by Steffen Moritz. Last updated 4 years ago.
3.4 match 16 stars 4.94 score 54 scriptsycroissant
pglm:Panel Generalized Linear Models
Estimation of panel models for glm-like models: this includes binomial models (logit and probit), count models (poisson and negbin) and ordered models (logit and probit), as described in: Baltagi (2013) Econometric Analysis of Panel Data <doi:10.1007/978-3-030-53953-5> Hsiao (2014) Analysis of Panel Data <doi:10.1017/CBO9781139839327> and Croissant and Millo (2018), Panel Data Econometrics with R <doi:10.1002/9781119504641>.
Maintained by Yves Croissant. Last updated 1 years ago.
3.8 match 4.34 score 158 scripts 1 dependentsstatimagcoll
RESI:Robust Effect Size Index (RESI) Estimation
Summarize model output using a robust effect size index. The index is introduced in Vandekar, Tao, & Blume (2020) <doi:10.1007/s11336-020-09698-2>.
Maintained by Megan Jones. Last updated 13 days ago.
3.8 match 4.30 score 20 scriptsrezamoammadi
liver:"Eating the Liver of Data Science"
Offers a suite of helper functions to simplify various data science techniques for non-experts. This package aims to enable individuals with only a minimal level of coding knowledge to become acquainted with these techniques in an accessible manner. Inspired by an ancient Persian idiom, we liken this process to "eating the liver of data science," suggesting a deep and intimate engagement with the field of data science. This package includes functions for tasks such as data partitioning for out-of-sample testing, calculating Mean Squared Error (MSE) to assess prediction accuracy, and data transformations (z-score and min-max). In addition to these helper functions, the 'liver' package also features several intriguing datasets valuable for multivariate analysis.
Maintained by Reza Mohammadi. Last updated 4 months ago.
4.0 match 4.00 score 67 scriptskeithmcnulty
peopleanalyticsdata:Data Sets for Keith McNulty's Handbook of Regression Modeling in People Analytics
Data sets for statistical inference modeling related to People Analytics. Contains various data sets from the book 'Handbook of Regression Modeling in People Analytics' by Keith McNulty (2020).
Maintained by Keith McNulty. Last updated 4 years ago.
4.0 match 6 stars 3.71 score 17 scriptsrudjer
REBayes:Empirical Bayes Estimation and Inference
Kiefer-Wolfowitz maximum likelihood estimation for mixture models and some other density estimation and regression methods based on convex optimization. See Koenker and Gu (2017) REBayes: An R Package for Empirical Bayes Mixture Methods, Journal of Statistical Software, 82, 1--26, <DOI:10.18637/jss.v082.i08>.
Maintained by Roger Koenker. Last updated 9 months ago.
3.8 match 3 stars 3.90 score 27 scripts 1 dependentsagbarnett
dobson:Data from the GLM Book by Dobson and Barnett
Example datasets from the book "An Introduction to Generalised Linear Models" (Year: 2018, ISBN:9781138741515) by Dobson and Barnett.
Maintained by Adrian Barnett. Last updated 6 years ago.
datasetsgeneralized-linear-models
3.6 match 3 stars 4.05 score 74 scriptsoskarallerslev
lifepack:Insurance Reserve Calculations
Calculates insurance reserves and equivalence premiums using advanced numerical methods, including the Runge-Kutta algorithm and product integrals for transition probabilities. This package is useful for actuarial analyses and life insurance modeling, facilitating accurate financial projections.
Maintained by Oskar Allerslev. Last updated 2 months ago.
4.1 match 3.30 scoreharrison4192
TidyConsultant:Tidy Consultant Universe
Loads the 5 packages in the Tidy Consultant Universe. This collection of packages is useful for anyone doing data science, data analysis, or quantitative consulting. The functions in these packages range from data cleaning, data validation, data binning, statistical modeling, and file exporting.
Maintained by Harrison Tietze. Last updated 9 months ago.
3.8 match 8 stars 3.60 score 2 scriptssunsmiling
PPtreeregViz:Projection Pursuit Regression Tree Visualization
It was developed as a tool for exploring 'PPTreereg' (Projection Pursuit TREE of REGression). It uses various projection pursuit indexes and 'XAI' (eXplainable Artificial Intelligence) methods to help understand the model by finding connections between the input variables and prediction values of the model. The 'KernelSHAP' (Aas, Jullum and Løland (2019) <arXiv:1903.10464>) algorithm was modified to fit ‘PPTreereg’, and some codes were modified from the 'shapr' package (Sellereite, Nikolai, and Martin Jullum (2020) <doi:10.21105/joss.02027>). The implemented methods help to explore the model at the single instance level as well as at the whole dataset level. Users can compare with other machine learning models by applying it to the 'DALEX' package of 'R'.
Maintained by HyunSun Cho. Last updated 1 years ago.
4.5 match 2 stars 3.00 score 3 scriptsdsy109
HoRM:Supplemental Functions and Datasets for "Handbook of Regression Methods"
Supplement for the book "Handbook of Regression Methods" by D. S. Young. Some datasets used in the book are included and documented. Wrapper functions are included that simplify the examples in the textbook, such as code for constructing a regressogram and expanding ANOVA tables to reflect the total sum of squares.
Maintained by Derek S. Young. Last updated 9 months ago.
regression-analysisregression-modelsshiny-apps
3.8 match 3.56 score 73 scriptsarbrazzale
cond:Approximate Conditional Inference for Logistic and Loglinear Models
Higher order likelihood-based inference for logistic and loglinear models.
Maintained by Alessandra R. Brazzale. Last updated 7 years ago.
3.6 match 3.51 score 27 scripts 2 dependentsmwaldstein
edgarWebR:SEC Filings Access
A set of methods to access and parse live filing information from the U.S. Securities and Exchange Commission (SEC - <https://www.sec.gov/>) including company and fund filings along with all associated metadata.
Maintained by Micah J Waldstein. Last updated 4 years ago.
1.9 match 78 stars 6.53 score 43 scriptscran
unifed:The Unifed Distribution
Probability functions, family for glm() and Stan code for working with the unifed distribution (Quijano Xacur, 2019; <doi:10.1186/s40488-019-0102-6>).
Maintained by Oscar Alberto Quijano Xacur. Last updated 3 years ago.
4.0 match 2.70 scorecran
HDtweedie:The Lasso for Tweedie's Compound Poisson Model Using an IRLS-BMD Algorithm
The Tweedie lasso model implements an iteratively reweighed least square (IRLS) strategy that incorporates a blockwise majorization decent (BMD) method, for efficiently computing solution paths of the (grouped) lasso and the (grouped) elastic net methods.
Maintained by Wei Qian. Last updated 3 years ago.
4.0 match 3 stars 2.59 score 43 scripts 1 dependentscran
splm:Econometric Models for Spatial Panel Data
ML and GM estimation and diagnostic testing of econometric models for spatial panel data.
Maintained by Giovanni Millo. Last updated 1 years ago.
3.4 match 10 stars 3.01 scorehrbrmstr
epidata:Tools to Retrieve Economic Policy Institute Data Library Extracts
The Economic Policy Institute (<http://www.epi.org/>) provides researchers, media, and the public with easily accessible, up-to-date, and comprehensive historical data on the American labor force. It is compiled from Economic Policy Institute analysis of government data sources. Use it to research wages, inequality, and other economic indicators over time and among demographic groups. Data is usually updated monthly.
Maintained by Bob Rudis. Last updated 5 years ago.
1.9 match 20 stars 5.45 score 28 scriptsjuvlac
camerondata:Datasets from "Microeconometrics: Methods and Applications" by Cameron and Trivedi
Quick and easy access to datasets that let you replicate the empirical examples in Cameron and Trivedi (2005) "Microeconometrics: Methods and Applications" (ISBN: 9780521848053).The data are available as soon as you install and load the package (lazy-loading) as data frames. The documentation includes reference to chapter sections and page numbers where the datasets are used.
Maintained by Juliana Vega-Lacorte. Last updated 3 years ago.
3.8 match 2.70 score 1 scriptsblunde1
agtboost:Adaptive and Automatic Gradient Boosting Computations
Fast and automatic gradient tree boosting designed to avoid manual tuning and cross-validation by utilizing an information theoretic approach. This makes the algorithm adaptive to the dataset at hand; it is completely automatic, and with minimal worries of overfitting. Consequently, the speed-ups relative to state-of-the-art implementations can be in the thousands while mathematical and technical knowledge required on the user are minimized.
Maintained by Berent Ånund Strømnes Lunde. Last updated 3 years ago.
5.6 match 1.72 score 52 scriptsgl-li
ExamPAData:Data Sets for Predictive Analytics Exam
Contains all data sets for Exam PA: Predictive Analytics at <https://exampa.net/>.
Maintained by Guanglai Li. Last updated 3 years ago.
8.5 match 1.00 scoreprabhanjan-tattar
ACSWR:A Companion Package for the Book "A Course in Statistics with R"
A book designed to meet the requirements of masters students. Tattar, P.N., Suresh, R., and Manjunath, B.G. "A Course in Statistics with R", J. Wiley, ISBN 978-1-119-15272-9.
Maintained by Prabhanjan Tattar. Last updated 10 years ago.
4.0 match 2.03 score 106 scriptsropengov
kelaopendata:Access open data from National social insurance institution of Finland
Designed to simplify and speed up access to open data from National social insurance institution of Finland (KELA) published at <https://www.avoindata.fi/data/fi/organization/kela>, the kelaopendata package offers researchers and analysts a set of tools to obtain data and metadata for a wide range of applications.
Maintained by Markus Kainu. Last updated 4 months ago.
dataopen-datasocial-security-data
3.3 match 1 stars 2.40 scoretorabi-uofm
SumcaVer1:Mean Square Prediction Error Estimation in Small Area Estimation
Estimation of mean squared prediction error of a small area predictor is provided. In particular, the recent method of Simple, Unified, Monte-Carlo Assisted approach for the mean squared prediction error estimation of small area predictor is provided. We also provide other existing methods of mean squared prediction error estimation such as jackknife method for the mixed logistic model.
Maintained by Mahmoud Torabi. Last updated 8 months ago.
7.4 match 1.00 scoreffqueiroz
robustbetareg:Robust Beta Regression
Robust estimators for the beta regression, useful for modeling bounded continuous data. Currently, four types of robust estimators are supported. They depend on a tuning constant which may be fixed or selected by a data-driven algorithm also implemented in the package. Diagnostic tools associated with the fitted model, such as the residuals and goodness-of-fit statistics, are implemented. Robust Wald-type tests are available. More details about robust beta regression are described in Maluf et al. (2022) <arXiv:2209.11315>.
Maintained by Felipe Queiroz. Last updated 2 years ago.
4.0 match 1.70 score 5 scriptsharryjalexander
ascentTraining:Ascent Training Datasets
Datasets to be used primarily in conjunction with Ascent training materials but also for the book 'SAMS Teach Yourself R in 24 Hours' (ISBN: 978-0-672-33848-9). Version 1.0-7 is largely for use with the book; however, version 1.1 has a much greater focus on use with training materials, whilst retaining compatibility with the book.
Maintained by Harry Alexander. Last updated 3 years ago.
6.0 match 1.00 score 2 scriptscran
ssym:Fitting Semi-Parametric log-Symmetric Regression Models
Set of tools to fit a semi-parametric regression model suitable for analysis of data sets in which the response variable is continuous, strictly positive, asymmetric and possibly, censored. Under this setup, both the median and the skewness of the response variable distribution are explicitly modeled by using semi-parametric functions, whose non-parametric components may be approximated by natural cubic splines or P-splines. Supported distributions for the model error include log-normal, log-Student-t, log-power-exponential, log-hyperbolic, log-contaminated-normal, log-slash, Birnbaum-Saunders and Birnbaum-Saunders-t distributions.
Maintained by Luis Hernando Vanegas. Last updated 2 years ago.
4.0 match 1.48 score 1 dependentshugometric
causalweight:Estimation Methods for Causal Inference Based on Inverse Probability Weighting
Various estimators of causal effects based on inverse probability weighting, doubly robust estimation, and double machine learning. Specifically, the package includes methods for estimating average treatment effects, direct and indirect effects in causal mediation analysis, and dynamic treatment effects. The models refer to studies of Froelich (2007) <doi:10.1016/j.jeconom.2006.06.004>, Huber (2012) <doi:10.3102/1076998611411917>, Huber (2014) <doi:10.1080/07474938.2013.806197>, Huber (2014) <doi:10.1002/jae.2341>, Froelich and Huber (2017) <doi:10.1111/rssb.12232>, Hsu, Huber, Lee, and Lettry (2020) <doi:10.1002/jae.2765>, and others.
Maintained by Hugo Bodory. Last updated 8 months ago.
3.5 match 2 stars 1.64 score 22 scriptscran
SMPracticals:Practicals for Use with Davison (2003) Statistical Models
Contains the datasets and a few functions for use with the practicals outlined in Appendix A of the book Statistical Models (Davison, 2003, Cambridge University Press), which can be found at <doi:10.1017/CBO9780511815850>.
Maintained by Alessandra R. Brazzale. Last updated 1 years ago.
3.8 match 1.48 score 1 dependentsimranshakoor
DataSetsUni:A Collection of Univariate Data Sets
A collection of widely used univariate data sets of various applied domains on applications of distribution theory. The functions allow researchers and practitioners to quickly, easily, and efficiently access and use these data sets. The data are related to different applied domains and as follows: Bio-medical, survival analysis, medicine, reliability analysis, hydrology, actuarial science, operational research, meteorology, extreme values, quality control, engineering, finance, sports and economics. The total 100 data sets are documented along with associated references for further details and uses.
Maintained by Muhammad Imran. Last updated 2 years ago.
5.3 match 1.00 score 1 scriptsrandhirbilkhu
eltr:Utilise Catastrophe Model Event Loss Table Outputs
Provides a tool to run Monte Carlo simulation of catastrophe model event loss tables, using a Poisson frequency and Beta severity distribution.
Maintained by Randhir Bilkhu. Last updated 4 years ago.
1.2 match 2 stars 4.48 score 4 scriptskainhofer
LifeInsuranceContracts:Framework for Traditional Life Insurance Contracts
Use of this package is deprecated. It has been renamed to 'LifeInsureR'.
Maintained by Reinhold Kainhofer. Last updated 1 years ago.
3.0 match 1.70 scorehrecht
censusapi:Retrieve Data from the Census APIs
A wrapper for the U.S. Census Bureau APIs that returns data frames of Census data and metadata. Available datasets include the Decennial Census, American Community Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, Population Estimates and Projections, and more.
Maintained by Hannah Recht. Last updated 11 days ago.
censuscensus-apicensus-datademographicsopen-data
0.5 match 174 stars 9.76 score 708 scripts 6 dependentscran
forward:Robust Analysis using Forward Search
Robust analysis using forward search in linear and generalized linear regression models, as described in Atkinson, A.C. and Riani, M. (2000), Robust Diagnostic Regression Analysis, First Edition. New York: Springer.
Maintained by Ken Beath. Last updated 6 months ago.
4.0 match 1.18 score 15 scriptsjbhasse
SystemicR:Monitoring Systemic Risk
The past decade has demonstrated an increased need to better understand risks leading to systemic crises. This framework offers scholars, practitioners and policymakers a useful toolbox to explore such risks in financial systems. Specifically, this framework provides popular econometric and network measures to monitor systemic risk and to measure the consequences of regulatory decisions. These systemic risk measures are based on the frameworks of Adrian and Brunnermeier (2016) <doi:10.1257/aer.20120555> and Billio, Getmansky, Lo and Pelizzon (2012) <doi:10.1016/j.jfineco.2011.12.010>.
Maintained by Jean-Baptiste Hasse. Last updated 5 years ago.
3.4 match 2 stars 1.30 score 1 scriptsagi-lab
SPLICE:Synthetic Paid Loss and Incurred Cost Experience (SPLICE) Simulator
An extension to the individual claim simulator called 'SynthETIC' (on CRAN), to simulate the evolution of case estimates of incurred losses through the lifetime of an insurance claim. The transactional simulation output now comprises key dates, and both claim payments and revisions of estimated incurred losses. An initial set of test parameters, designed to mirror the experience of a real insurance portfolio, were set up and applied by default to generate a realistic test data set of incurred histories (see vignette). However, the distributional assumptions used to generate this data set can be easily modified by users to match their experiences. Reference: Avanzi B, Taylor G, Wang M (2021) "SPLICE: A Synthetic Paid Loss and Incurred Cost Experience Simulator" <arXiv:2109.04058>.
Maintained by Melantha Wang. Last updated 1 years ago.
0.8 match 6 stars 5.58 score 14 scriptsvanzanden
ggsolvencyii:A 'ggplot2'-Plot of Composition of Solvency II SCR: SF and IM
An implementation of 'ggplot2'-methods to present the composition of Solvency II Solvency Capital Requirement (SCR) as a series of concentric circle-parts. Solvency II (Solvency 2) is European insurance legislation, coming in force by the delegated acts of October 10, 2014. <https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ%3AL%3A2015%3A012%3ATOC>. Additional files, defining the structure of the Standard Formula (SF) method of the SCR-calculation are provided. The structure files can be adopted for localization or for insurance companies who use Internal Models (IM). Options are available for combining smaller components, horizontal and vertical scaling, rotation, and plotting only some circle-parts. With outlines and connectors several SCR-compositions can be compared, for example in ORSA-scenarios (Own Risk and Solvency Assessment).
Maintained by Marco van Zanden. Last updated 6 years ago.
0.8 match 3 stars 5.58 score 63 scriptscran
datarobot:'DataRobot' Predictive Modeling API
For working with the 'DataRobot' predictive modeling platform's API <https://www.datarobot.com/>.
Maintained by AJ Alon. Last updated 1 years ago.
1.2 match 2 stars 3.48 scorep0bs
p0bservations:Assorted Functions and Observations by P0bs
Provides assorted functions by p0bs.
Maintained by Robin Penfold. Last updated 4 months ago.
1.8 match 2.30 score 1 scriptsrainers48
tsapp:Time Series, Analysis and Application
Accompanies the book Rainer Schlittgen and Cristina Sattarhoff (2020) <https://www.degruyter.com/view/title/575978> "Angewandte Zeitreihenanalyse mit R, 4. Auflage" . The package contains the time series and functions used therein. It was developed over many years teaching courses about time series analysis.
Maintained by Rainer Schlittgen. Last updated 3 years ago.
4.0 match 1.00 score 1 scriptscran
tea:Threshold Estimation Approaches
Different approaches for selecting the threshold in generalized Pareto distributions. Most of them are based on minimizing the AMSE-criterion or at least by reducing the bias of the assumed GPD-model. Others are heuristically motivated by searching for stable sample paths, i.e. a nearly constant region of the tail index estimator with respect to k, which is the number of data in the tail. The third class is motivated by graphical inspection. In addition, a sequential testing procedure for GPD-GoF-tests is also implemented here.
Maintained by Johannes Ossberger. Last updated 5 years ago.
3.8 match 1.00 scorespedygiorgio
mbbefd:Maxwell Boltzmann Bose Einstein Fermi Dirac Distribution and Destruction Rate Modelling
Distributions that are typically used for exposure rating in general insurance, in particular to price reinsurance contracts. The vignette shows code snippets to fit the distribution to empirical data. See, e.g., Bernegger (1997) <doi:10.2143/AST.27.1.563208> freely available on-line.
Maintained by Christophe Dutang. Last updated 22 days ago.
actuarialdestruction-rate-modelingreinsurancecpp
0.5 match 15 stars 7.05 score 99 scriptsextremestats
DATAstudio:The Research Data Warehouse of Miguel de Carvalho
Pulls together a collection of datasets from Miguel de Carvalho research articles. Including, for example: - de Carvalho (2012) <doi:10.1016/j.jspi.2011.08.016>; - de Carvalho et al (2012) <doi:10.1080/03610926.2012.709905>; - de Carvalho et al (2012) <doi:10.1016/j.econlet.2011.09.007>); - de Carvalho and Davison (2014) <doi:10.1080/01621459.2013.872651>; - de Carvalho and Rua (2017) <doi:10.1016/j.ijforecast.2015.09.004>.
Maintained by Miguel de Carvalho. Last updated 3 years ago.
3.6 match 1.00 score 2 scriptsextremestats
spearmanCI:Jackknife Euclidean / Empirical Likelihood Inference for Spearman's Rho
Functions for conducting jackknife Euclidean / empirical likelihood inference for Spearman's rho (de Carvalho and Marques (2012) <doi:10.1080/10920277.2012.10597644>).
Maintained by Miguel de Carvalho. Last updated 10 months ago.
3.6 match 1.00 score 2 scriptsmattheaphy
offsetreg:An Extension of 'Tidymodels' Supporting Offset Terms
Extend the 'tidymodels' ecosystem <https://www.tidymodels.org/> to enable the creation of predictive models with offset terms. Models with offsets are most useful when working with count data or when fitting an adjustment model on top of an existing model with a prior expectation. The former situation is common in insurance where data is often weighted by exposures. The latter is common in life insurance where industry mortality tables are often used as a starting point for setting assumptions.
Maintained by Matt Heaphy. Last updated 21 days ago.
0.8 match 2 stars 4.48 score 4 scriptsvisbanking
fdicdata:Accessing FDIC Bank Data
A system provides a set of functions for working with data from the Federal Deposit Insurance Corporation (FDIC), including retrieving financial data for FDIC-insured institutions and accessing the data taxonomy.
Maintained by Ugur Dar. Last updated 2 years ago.
0.8 match 9 stars 3.65 score 3 scriptsguillaumebiessy
WH:Enhanced Implementation of Whittaker-Henderson Smoothing
An enhanced implementation of Whittaker-Henderson smoothing for the gradation of one-dimensional and two-dimensional actuarial tables used to quantify Life Insurance risks. 'WH' is based on the methods described in Biessy (2023) <doi:10.48550/arXiv.2306.06932>. Among other features, it generalizes the original smoothing algorithm to maximum likelihood estimation, automatically selects the smoothing parameter(s) and extrapolates beyond the range of data.
Maintained by Guillaume Biessy. Last updated 4 months ago.
actuarial-sciencebayesian-methodsmortality-estimationsmoothing-methods
0.5 match 9 stars 5.35 score 6 scriptsashesitr
reservr:Fit Distributions and Neural Networks to Censored and Truncated Data
Define distribution families and fit them to interval-censored and interval-truncated data, where the truncation bounds may depend on the individual observation. The defined distributions feature density, probability, sampling and fitting methods as well as efficient implementations of the log-density log f(x) and log-probability log P(x0 <= X <= x1) for use in 'TensorFlow' neural networks via the 'tensorflow' package. Allows training parametric neural networks on interval-censored and interval-truncated data with flexible parameterization. Applications include Claims Development in Non-Life Insurance, e.g. modelling reporting delay distributions from incomplete data, see Bücher, Rosenstock (2022) <doi:10.1007/s13385-022-00314-4>.
Maintained by Alexander Rosenstock. Last updated 9 months ago.
0.5 match 5 stars 5.35 score 9 scriptsropensci
rfema:Access the openFEMA API
`rfema` allows users to access The Federal Emergency Management Agency's (FEMA) publicly available data through their API. The package provides a set of functions to easily navigate and access data from the National Flood Insurance Program along with FEMA's various disaster aid programs, including the Hazard Mitigation Grant Program, the Public Assistance Grant Program, and the Individual Assistance Grant Program.
Maintained by Dylan Turner. Last updated 24 days ago.
0.5 match 9 stars 4.73 score 5 scriptswindwill
cascsim:Casualty Actuarial Society Individual Claim Simulator
It is an open source insurance claim simulation engine sponsored by the Casualty Actuarial Society. It generates individual insurance claims including open claims, reopened claims, incurred but not reported claims and future claims. It also includes claim data fitting functions to help set simulation assumptions. It is useful for claim level reserving analysis. Parodi (2013) <https://www.actuaries.org.uk/documents/triangle-free-reserving-non-traditional-framework-estimating-reserves-and-reserve-uncertainty>.
Maintained by Kailan Shang. Last updated 5 years ago.
0.8 match 2.99 score 98 scriptstechtonique
esgtoolkit:Toolkit for Monte Carlo Simulations
A toolkit for Monte Carlo Simulations in Finance, Economics, Insurance, Physics. Multiple simulation models can be created by combining building blocks provided in the package.
Maintained by T. Moudiki. Last updated 1 months ago.
diffusion-modeldiffusion-modelsmonte-carlo-methodsmonte-carlo-simulationmontecarlo-simulationscenario-analysisscenario-creatorscenario-generationsimulationstochastic-differential-equationsstochastic-processesstochastic-simulationcpp
0.5 match 11 stars 3.97 score 28 scriptsaadler
MBBEFDLite:Statistical Functions for the Maxwell-Boltzmann-Bose-Einstein-Fermi-Dirac (MBBEFD) Family of Distributions
Provides probability mass, distribution, quantile, random variate generation, and method-of-moments parameter fitting for the MBBEFD family of distributions used in insurance modeling as described in Bernegger (1997) <doi:10.2143/AST.27.1.563208> without any external dependencies.
Maintained by Avraham Adler. Last updated 1 months ago.
0.5 match 1 stars 3.65 scoremehdichelh
eiopaR:Access to RFR (Risk-Free Rate) Curves Produced by the EIOPA
Provides EIOPA (European Insurance And Occupational Pensions Authority) risk-free rates. Please note that the author of this package is not affiliated with EIOPA. The data is accessed through a REST API available at <https://mehdiechchelh.com/api/>.
Maintained by Mehdi Echchelh. Last updated 4 years ago.
0.5 match 3 stars 3.18 score 2 scriptsambarish-chattopadhyay
FSM:Finite Selection Model
Randomized and balanced allocation of units to treatment groups using the Finite Selection Model (FSM). The FSM was originally proposed and developed at the RAND corporation by Carl Morris to enhance the experimental design for the now famous Health Insurance Experiment. See Morris (1979) <doi:10.1016/0304-4076(79)90053-8> for details on the original version of the FSM.
Maintained by Ambarish Chattopadhyay. Last updated 4 years ago.
0.5 match 2.00 score 3 scriptscran
DCL:Claims Reserving under the Double Chain Ladder Model
Statistical modelling and forecasting in claims reserving in non-life insurance under the Double Chain Ladder framework by Martinez-Miranda, Nielsen and Verrall (2012).
Maintained by Maria Dolores Martinez-Miranda. Last updated 3 years ago.
0.5 match 1 stars 1.00 score