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alanarnholt

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.

34.0 match 7 stars 9.11 score 1.3k scripts 6 dependents

economic

realtalk:Price index data for the US economy

Makes it easy to use US price index data like the CPI.

Maintained by Ben Zipperer. Last updated 4 days ago.

cpidatainflationprices

62.3 match 5 stars 3.51 score 10 scripts

sbgraves237

Ecdat:Data Sets for Econometrics

Data sets for econometrics, including political science.

Maintained by Spencer Graves. Last updated 4 months ago.

22.4 match 2 stars 7.25 score 740 scripts 3 dependents

tomaspinall

NFCP:N-Factor Commodity Pricing Through Term Structure Estimation

Commodity pricing models are (systems of) stochastic differential equations that are utilized for the valuation and hedging of commodity contingent claims (i.e. derivative products on the commodity) and other commodity related investments. Commodity pricing models that capture market dynamics are of great importance to commodity market participants in order to exercise sound investment and risk-management strategies. Parameters of commodity pricing models are estimated through maximum likelihood estimation, using available term structure futures data of a commodity. 'NFCP' (n-factor commodity pricing) provides a framework for the modeling, parameter estimation, probabilistic forecasting, option valuation and simulation of commodity prices through state space and Monte Carlo methods, risk-neutral valuation and Kalman filtering. 'NFCP' allows the commodity pricing model to consist of n correlated factors, with both random walk and mean-reverting elements. The n-factor commodity pricing model framework was first presented in the work of Cortazar and Naranjo (2006) <doi:10.1002/fut.20198>. Examples presented in 'NFCP' replicate the two-factor crude oil commodity pricing model presented in the prolific work of Schwartz and Smith (2000) <doi:10.1287/mnsc.46.7.893.12034> with the approximate term structure futures data applied within this study provided in the 'NFCP' package.

Maintained by Thomas Aspinall. Last updated 3 years ago.

25.6 match 5 stars 4.40 score 4 scripts

joshuaulrich

quantmod:Quantitative Financial Modelling Framework

Specify, build, trade, and analyse quantitative financial trading strategies.

Maintained by Joshua M. Ulrich. Last updated 14 days ago.

algorithmic-tradingchartingdata-importfinancetime-series

6.6 match 839 stars 16.17 score 8.1k scripts 343 dependents

felixfan

FinCal:Time Value of Money, Time Series Analysis and Computational Finance

Package for time value of money calculation, time series analysis and computational finance.

Maintained by Felix Yanhui Fan. Last updated 8 years ago.

15.0 match 23 stars 6.02 score 203 scripts 1 dependents

topepo

caret:Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Maintained by Max Kuhn. Last updated 3 months ago.

3.8 match 1.6k stars 19.24 score 61k scripts 303 dependents

khamidieh

RND:Risk Neutral Density Extraction Package

Extract the implied risk neutral density from options using various methods.

Maintained by Kam Hamidieh. Last updated 8 years ago.

23.4 match 1 stars 2.80 score 70 scripts

pik-piam

remind2:The REMIND R package (2nd generation)

Contains the REMIND-specific routines for data and model output manipulation.

Maintained by Renato Rodrigues. Last updated 6 days ago.

7.0 match 8.88 score 161 scripts 5 dependents

braverock

FinancialInstrument:Financial Instrument Model Infrastructure for R

Infrastructure for defining meta-data and relationships for financial instruments.

Maintained by Ross Bennett. Last updated 7 years ago.

10.7 match 19 stars 4.99 score 102 scripts

pik-piam

piamInterfaces:Project specific interfaces to REMIND / MAgPIE

Project specific interfaces to REMIND / MAgPIE.

Maintained by Falk Benke. Last updated 2 days ago.

8.0 match 6.63 score 38 scripts 7 dependents

pik-piam

magpie4:MAgPIE outputs R package for MAgPIE version 4.x

Common output routines for extracting results from the MAgPIE framework (versions 4.x).

Maintained by Benjamin Leon Bodirsky. Last updated 2 days ago.

6.0 match 2 stars 7.87 score 254 scripts 9 dependents

a91quaini

intrinsicFRP:An R Package for Factor Model Asset Pricing

Functions for evaluating and testing asset pricing models, including estimation and testing of factor risk premia, selection of "strong" risk factors (factors having nonzero population correlation with test asset returns), heteroskedasticity and autocorrelation robust covariance matrix estimation and testing for model misspecification and identification. The functions for estimating and testing factor risk premia implement the Fama-MachBeth (1973) <doi:10.1086/260061> two-pass approach, the misspecification-robust approaches of Kan-Robotti-Shanken (2013) <doi:10.1111/jofi.12035>, and the approaches based on tradable factor risk premia of Quaini-Trojani-Yuan (2023) <doi:10.2139/ssrn.4574683>. The functions for selecting the "strong" risk factors are based on the Oracle estimator of Quaini-Trojani-Yuan (2023) <doi:10.2139/ssrn.4574683> and the factor screening procedure of Gospodinov-Kan-Robotti (2014) <doi:10.2139/ssrn.2579821>. The functions for evaluating model misspecification implement the HJ model misspecification distance of Kan-Robotti (2008) <doi:10.1016/j.jempfin.2008.03.003>, which is a modification of the prominent Hansen-Jagannathan (1997) <doi:10.1111/j.1540-6261.1997.tb04813.x> distance. The functions for testing model identification specialize the Kleibergen-Paap (2006) <doi:10.1016/j.jeconom.2005.02.011> and the Chen-Fang (2019) <doi:10.1111/j.1540-6261.1997.tb04813.x> rank test to the regression coefficient matrix of test asset returns on risk factors. Finally, the function for heteroskedasticity and autocorrelation robust covariance estimation implements the Newey-West (1994) <doi:10.2307/2297912> covariance estimator.

Maintained by Alberto Quaini. Last updated 8 months ago.

factor-modelsfactor-selectionfinanceidentification-testsmisspecificationrcpparmadillorisk-premiumopenblascppopenmp

10.2 match 7 stars 4.45 score 1 scripts

tidymodels

modeldata:Data Sets Useful for Modeling Examples

Data sets used for demonstrating or testing model-related packages are contained in this package.

Maintained by Max Kuhn. Last updated 5 months ago.

3.8 match 22 stars 10.66 score 2.2k scripts 17 dependents

kurthornik

tseries:Time Series Analysis and Computational Finance

Time series analysis and computational finance.

Maintained by Kurt Hornik. Last updated 6 months ago.

fortranopenblas

3.5 match 4 stars 11.22 score 10k scripts 289 dependents

tiledb-inc

tiledbcloud:TileDB Cloud Platform R Client Package

The TileDB Cloud Platform API Client Package offers access to the TileDB Cloud service.

Maintained by John Kerl. Last updated 8 months ago.

6.0 match 1 stars 5.22 score 92 scripts

phil8192

obAnalytics:Limit Order Book Analytics

Data processing, visualisation and analysis of Limit Order Book event data.

Maintained by Philip Stubbings. Last updated 6 years ago.

bitcoinlimit-order-booktradingvisualisation

4.9 match 152 stars 6.36 score 30 scripts

satopaa

metaggR:Calculate the Knowledge-Weighted Estimate

According to a phenomenon known as "the wisdom of the crowds," combining point estimates from multiple judges often provides a more accurate aggregate estimate than using a point estimate from a single judge. However, if the judges use shared information in their estimates, the simple average will over-emphasize this common component at the expense of the judges’ private information. Asa Palley & Ville Satopää (2021) "Boosting the Wisdom of Crowds Within a Single Judgment Problem: Selective Averaging Based on Peer Predictions" <https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=3504286> proposes a procedure for calculating a weighted average of the judges’ individual estimates such that resulting aggregate estimate appropriately combines the judges' collective information within a single estimation problem. The authors use both simulation and data from six experimental studies to illustrate that the weighting procedure outperforms existing averaging-like methods, such as the equally weighted average, trimmed average, and median. This aggregate estimate -- know as "the knowledge-weighted estimate" -- inputs a) judges' estimates of a continuous outcome (E) and b) predictions of others' average estimate of this outcome (P). In this R-package, the function knowledge_weighted_estimate(E,P) implements the knowledge-weighted estimate. Its use is illustrated with a simple stylized example and on real-world experimental data.

Maintained by Ville Satopää. Last updated 3 years ago.

10.0 match 1 stars 2.85 score 14 scripts

steve-the-bayesian

bsts:Bayesian Structural Time Series

Time series regression using dynamic linear models fit using MCMC. See Scott and Varian (2014) <DOI:10.1504/IJMMNO.2014.059942>, among many other sources.

Maintained by Steven L. Scott. Last updated 1 years ago.

cpp

4.0 match 33 stars 6.54 score 338 scripts 3 dependents

yuimaproject

yuima:The YUIMA Project Package for SDEs

Simulation and Inference for SDEs and Other Stochastic Processes.

Maintained by Stefano M. Iacus. Last updated 3 days ago.

openblascpp

3.6 match 9 stars 7.26 score 92 scripts 2 dependents

dvmlls

bdscale:Remove Weekends and Holidays from ggplot2 Axes

Provides a continuous date scale, omitting weekends and holidays.

Maintained by Dave Mills. Last updated 9 years ago.

4.9 match 10 stars 5.10 score 25 scripts

r-forge

car:Companion to Applied Regression

Functions to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage, 2019.

Maintained by John Fox. Last updated 5 months ago.

1.5 match 15.29 score 43k scripts 901 dependents

alanarnholt

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 scripts

pik-piam

mredgebuildings:Prepare data to be used by the EDGE-Buildings model

Prepare data to be used by the EDGE-Buildings model.

Maintained by Robin Hasse. Last updated 2 days ago.

5.6 match 3.72 score

tobiaskley

quantspec:Quantile-Based Spectral Analysis of Time Series

Methods to determine, smooth and plot quantile periodograms for univariate and multivariate time series.

Maintained by Tobias Kley. Last updated 9 years ago.

cpp

3.4 match 10 stars 5.84 score 46 scripts 1 dependents

alanarnholt

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 scripts

jaredlander

resumer:Build Resumes with R

Using a CSV, LaTeX and R to easily build attractive resumes.

Maintained by Jared Lander. Last updated 3 years ago.

3.5 match 70 stars 5.12 score 19 scripts

mihai-sysbio

glpkAPI:R Interface to C API of GLPK

R Interface to C API of GLPK, depends on GLPK Version >= 4.42.

Maintained by Mihail Anton. Last updated 2 years ago.

glpk

3.0 match 5.96 score 51 scripts 12 dependents