ols_diagnost: Compute diagnostics for OLS models

Description Usage Arguments Value References

View source: R/RcppExports.R

Description

Compute OLS diagnostics such as R^2, adjusted R^2, AIC, etc.

Usage

1

Arguments

y

Numeric vector.

x

Numeric matrix.

Value

A list:

beta

Point estimates of OLS regression.

beta_cov

Covariance matrix of point estimates.

R^2

The R^2 statistic from OLS regression.

Adj.R^2

The adjusted R^2 staistic from OLS regression.

F-stat

The computed F-statistic.

df1

First degress of freedom for F-statistic.

df2

Second degrees of freedom for F-staitisc.

AIC_c

The AIC_c criterion by Hurvich and Tsai (1989)

AIC

The AIC criterion by Akaike (1974)

BIC

The BIC criterion by Schwarz and Gideon (1978)

References

Akaike, H. (1974). "A new look at the statistical model identification", IEEE Transactions on Automatic Control, 19 (6): 716–723.

Hurvich, C. M., and Tsai, C.-L. (1989). "Regression and time series model selection in small samples", Biometrika, 76(2): 297–307,

Schwarz, G.(1978). "Estimating the dimension of a model", Annals of Statistics, 6 (2): 461–464.


lpirfs documentation built on March 24, 2021, 1:10 a.m.