lm_summary: lm_summary

In leyaozh/lm.hw4: Linear Regression

Description

Summary method for the result list of lm_fit.

Usage

lm_summary(object, correlation = FALSE)

Arguments

object	a result of lm_fit; only support cases when the input response variable is a vector or a n * 1 matrix and the method for fitting the model is "qr".
correlation	logical;if TRUE, the correlation matrix of the estimated parameters is returned and printed.

Value

lm_summary returns a list containing following response values.

residuals	a vector of residuals, which equals response minus fitted values.
coefficients	a named vector of coefficients.
aliased	a named logical vector showing if the original coefficients are aliased.
sigma	the square root of the estimated variance of the random error
df	degrees of freedom, a 3-vector (p, n-p, p*), the first being the number of non-aliased coefficients, the last being the total number of coefficients.
fstatistics	(for models including non-intercept terms) a 3-vector with the value of the F-statistic with its numerator and denominator degrees of freedom.
r.squared	R^2, the fraction of variance explained by the model.
adj.r.squared	adjusted R^2.
cov.unscaled	a p * p matrix covariances of the coefficients.
correlation	a p * p correlation matrix of the coefficients.

Examples

n = 10; p = 5; q = 2;
x = matrix(rnorm(n * p), n, p) # no intercept
y1 = rnorm(n)
y2 = matrix(rnorm(n * q), n, q)

z1 = lm_fit(x = x, y = y1)
z2 = lm_fit(x = x, y = y2)

# no correlation matrix is returned
z_summary1 = lm_summary(z1)
z_summary2 = lm_summary(z1, correlation = TRUE) #return correlation matrix
# lm_summary function doesn't support cases lm_summary(z2)
# because the response value y2 is a matrix with more than 1 columns.

leyaozh/lm.hw4 documentation built on Dec. 3, 2019, 7:18 a.m.