summary.plr: Summarizing Polygonal Linear Regression

In psda: Polygonal Symbolic Data Analysis

Description

summary method for class plr.

Usage

## S3 method for class 'plr'
summary(object, digits = max(3L, getOption("digits") - 3L),
  ...)

Arguments

object	an object of the class plr, usually, a result of a call to plr.
digits	a non-null value for digits specifies the minimum number of significant digits to be printed in values.
...	further arguments passed to or from other methods.

Value

residuals calculated as the response variable minus the fitted values.

sigma the given by square root of the estimated variance of the random error

σ^2 = \frac{∑{i = 1}^{n} (y_i - \hat{y}_i)^2}{n - p - 1}

where p is two times the number of independent variables.

call the matched call.

aliased named logical vector showing if the original coefficients are aliased.

terms the terms.

coefficients a p x 4 matrix with columns for the estimated coefficient, its standard error, z-statistic and corresponding (two-sided) p-value.

Examples

yp <- psim(50, 10) #simulate 50 polygons of 10 sides
xp1 <- psim(50, 10) #simulate 50 polygons of 10 sides
xp2 <- psim(50, 10) #simulate 50 polygons of 10 sides
e <- new.env()
e$yp <- yp
e$xp1 <- xp1
e$xp2 <- xp2
fit <- plr(yp~xp1 + xp2, data = e)
s <- summary(fit) 

psda documentation built on July 1, 2020, 6:10 p.m.