In rsquaredacademy/report: Generate Reports from Rsquared Academy Packages

knitr::opts_chunk$set(echo = FALSE)

suppressWarnings(suppressMessages(library(olsrr, quietly = TRUE)))

Regression

ols_regress(model)

Residual QQ Plot

ols_plot_resid_qq(model)

Residual Normality Test

ols_test_normality(model)

Correlation between observed residuals and expected residuals under normality.

ols_test_correlation(model)

Residual vs Fitted Values Plot

ols_plot_resid_fit(model)

Residual Histogram

ols_plot_resid_hist(model)

Cook's D Bar Plot

ols_plot_cooksd_bar(model)

Cook's D Chart

ols_plot_cooksd_chart(model)

DFBETAs Panel

ols_plot_dfbetas(model)

DFFITS Plot

ols_plot_dffits(model)

Studentized Residual Plot

ols_plot_resid_stud(model)

Standardized Residual Chart

ols_plot_resid_stand(model)

Studentized Residuals vs Leverage Plot

ols_plot_resid_lev(model)

Deleted Studentized Residual vs Fitted Values Plot

ols_plot_resid_stud_fit(model)

Hadi Plot

ols_plot_hadi(model)

Potential Residual Plot

ols_plot_resid_pot(model)

Collinearity Diagnostics

VIF

model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars)
ols_vif_tol(model)

Condition Index

model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars)
ols_eigen_cindex(model)

Collinearity Diagnostics

model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars)
ols_coll_diag(model)

Residual Fit Spread Plot

ols_plot_resid_fit_spread(model)

Part & Partial Correlations

ols_correlations(model)

Observed vs Predicted Plot

ols_plot_obs_fit(model)

Diagnostics Panel

ols_plot_diagnostics(model)

Added Variable Plot

ols_plot_added_variable(model)

Residual Plus Component Plot

ols_plot_comp_plus_resid(model)

Breusch Pagan Test

ols_test_breusch_pagan(model)

Score Test

ols_test_score(model)

F Test

ols_test_f(model)

All Possible Regression

ols_step_all_possible(model)

Plot

k <- ols_step_all_possible(model)
plot(k)

Best Subset Regression

ols_step_best_subset(model)

Plot

k <- ols_step_best_subset(model)
plot(k)

Stepwise AIC Forward Regression

Variable Selection

ols_step_forward_aic(model)

Plot

k <- ols_step_forward_aic(model)
plot(k)

Stepwise AIC Backward Regression

Variable Selection

k <- ols_step_backward_aic(model)
k

Plot

k <- ols_step_backward_aic(model)
plot(k)

Stepwise AIC Regression

Variable Selection

ols_step_both_aic(model)

Plot

k <- ols_step_both_aic(model)
plot(k)

rsquaredacademy/report documentation built on Sept. 29, 2019, 12:14 a.m.