ols_diagnost: Compute diagnostics for OLS models

In lpirfs: Local Projections Impulse Response Functions

Compute diagnostics for OLS models

Description

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

Usage

ols_diagnost(y, x)

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 July 9, 2023, 6:35 p.m.