Showing 7 of total 7 results (show query)
laresbernardo
lares:Analytics & Machine Learning Sidekick
Auxiliary package for better/faster analytics, visualization, data mining, and machine learning tasks. With a wide variety of family functions, like Machine Learning, Data Wrangling, Marketing Mix Modeling (Robyn), Exploratory, API, and Scrapper, it helps the analyst or data scientist to get quick and robust results, without the need of repetitive coding or advanced R programming skills.
Maintained by Bernardo Lares. Last updated 1 months ago.
analyticsapiautomationautomldata-sciencedescriptive-statisticsh2omachine-learningmarketingmmmpredictive-modelingpuzzlerlanguagerobynvisualization
233 stars 9.92 score 185 scripts 1 dependents
dmphillippo
multinma:Bayesian Network Meta-Analysis of Individual and Aggregate Data
Network meta-analysis and network meta-regression models for aggregate data, individual patient data, and mixtures of both individual and aggregate data using multilevel network meta-regression as described by Phillippo et al. (2020) <doi:10.1111/rssa.12579>. Models are estimated in a Bayesian framework using 'Stan'.
Maintained by David M. Phillippo. Last updated 3 days ago.
35 stars 9.34 score 163 scripts
flr
FLCore:Core Package of FLR, Fisheries Modelling in R
Core classes and methods for FLR, a framework for fisheries modelling and management strategy simulation in R. Developed by a team of fisheries scientists in various countries. More information can be found at <http://flr-project.org/>.
Maintained by Iago Mosqueira. Last updated 9 days ago.
fisheriesflrfisheries-modelling
16 stars 8.78 score 956 scripts 23 dependents
pilaboratory
sads:Maximum Likelihood Models for Species Abundance Distributions
Maximum likelihood tools to fit and compare models of species abundance distributions and of species rank-abundance distributions.
Maintained by Paulo I. Prado. Last updated 1 years ago.
23 stars 8.66 score 244 scripts 3 dependentsflr
FLa4a:A Simple and Robust Statistical Catch at Age Model
A simple and robust statistical Catch at Age model that is specifically designed for stocks with intermediate levels of data quantity and quality.
Maintained by Ernesto Jardim. Last updated 8 days ago.
12 stars 6.71 score 177 scripts 2 dependents
vladimirholy
gasmodel:Generalized Autoregressive Score Models
Estimation, forecasting, and simulation of generalized autoregressive score (GAS) models of Creal, Koopman, and Lucas (2013) <doi:10.1002/jae.1279> and Harvey (2013) <doi:10.1017/cbo9781139540933>. Model specification allows for various data types and distributions, different parametrizations, exogenous variables, joint and separate modeling of exogenous variables and dynamics, higher score and autoregressive orders, custom and unconditional initial values of time-varying parameters, fixed and bounded values of coefficients, and missing values. Model estimation is performed by the maximum likelihood method.
Maintained by Vladimír Holý. Last updated 1 years ago.
14 stars 5.45 score 2 scripts
tpetzoldt
FAmle:Maximum Likelihood and Bayesian Estimation of Univariate Probability Distributions
Estimate parameters of univariate probability distributions with maximum likelihood and Bayesian methods.
Maintained by Thomas Petzoldt. Last updated 3 years ago.
3.81 score 13 scripts