Compute diagnostics for OLS models
Compute OLS diagnostics such as R^2, adjusted R^2, AIC, etc.
ols_diagnost(y, x)
y |
Numeric vector. |
x |
Numeric matrix. |
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) |
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.
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