Package: EcoMetrics 0.1.1

EcoMetrics: Econometrics Model Building

An intuitive and user-friendly package designed to aid undergraduate students in understanding and applying econometric methods in their studies, Tailored specifically for Econometrics and Regression Modeling courses, it provides a practical toolkit for modeling and analyzing econometric data with detailed inference capabilities.

Authors:Mutua Kilai [aut, cre]

EcoMetrics_0.1.1.tar.gz
EcoMetrics_0.1.1.zip(r-4.5)EcoMetrics_0.1.1.zip(r-4.4)EcoMetrics_0.1.1.zip(r-4.3)
EcoMetrics_0.1.1.tgz(r-4.5-any)EcoMetrics_0.1.1.tgz(r-4.4-any)EcoMetrics_0.1.1.tgz(r-4.3-any)
EcoMetrics_0.1.1.tar.gz(r-4.5-noble)EcoMetrics_0.1.1.tar.gz(r-4.4-noble)
EcoMetrics_0.1.1.tgz(r-4.4-emscripten)EcoMetrics_0.1.1.tgz(r-4.3-emscripten)
EcoMetrics.pdf |EcoMetrics.html✨
EcoMetrics/json (API)

# Install 'EcoMetrics' in R:

install.packages('EcoMetrics', repos = c('https://mutuasam.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

eduperform - Student Performance Data
keconomy - Kenya Unemployment Rate and GDP Growth rate for 1999-2023

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 266 downloads 18 exports 79 dependencies

Last updated 1 months agofrom:73dd798f33. Checks:8 OK. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Feb 28 2025
R-4.5-win	OK	Feb 28 2025
R-4.5-mac	OK	Feb 28 2025
R-4.5-linux	OK	Feb 28 2025
R-4.4-win	OK	Feb 28 2025
R-4.4-mac	OK	Feb 28 2025
R-4.3-win	OK	Feb 28 2025
R-4.3-mac	OK	Feb 28 2025

Exports:ACF_PLOT autocorrelation_assumption best_arima check_model_sig check_stationarity fit_arima get_coefficients_variance get_confint get_significant_predictors heteroscedasticity_assumption multicollinearity_assumption normality_assumption ols_model ols_model_sig ols_model_stats PACF_PLOT predict_dep_var select_optimal_model

Dependencies:abind backports boot broom car carData cli colorspace cowplot cpp11 curl Deriv doBy dplyr fansi farver forecast Formula fracdiff generics ggplot2 glue gtable insight isoband jsonlite labeling lattice lifecycle lme4 lmtest magrittr MASS Matrix MatrixModels mgcv microbenchmark minqa modelr moments munsell nlme nloptr nnet numDeriv pbkrtest pillar pkgconfig purrr quadprog quantmod quantreg R6 rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack reformulas rlang scales SparseM stringi stringr survival tibble tidyr tidyselect timeDate tseries TTR urca utf8 vctrs viridisLite withr xts zoo

Citation

Readme and manuals

Help Manual

Help page	Topics
Plots ACF of a univariate time series	ACF_PLOT
Check model for residual independence	autocorrelation_assumption
Select Optimal Model based on BIC	best_arima
Checking Overall Model Significance	check_model_sig
Check Series for Weak Stationarity	check_stationarity
Student Performance Data	eduperform
Fit ARIMA models to univariate data	fit_arima
Get variance of the model coefficients	get_coefficients_variance
Confidence Intervals of Model Parameters	get_confint
Obtaining only significant predictors from a model	get_significant_predictors
Checking heteroscedasticity assumption	heteroscedasticity_assumption
Kenya Unemployment Rate and GDP Growth rate for 1999-2023	keconomy
Multicollinearity Assumption	multicollinearity_assumption
Checking normality of residuals	normality_assumption
Fitting a simple or multiple linear regression	ols_model
F-statistic attributes	ols_model_sig
Model Summary Statistics	ols_model_stats
Plots PACF of a univariate time series	PACF_PLOT
Prediction from new observations	predict_dep_var
Choosing Best Model Based on AIC, BIC and Adjusted R Squared	select_optimal_model

Package: EcoMetrics 0.1.1

EcoMetrics: Econometrics Model Building

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)