testDiagnostics: Test assumptions of least squares
In sfeuerriegel/ResearchGroupTools: Collection of Custom Helper Functions
Description
Usage
Arguments
Value
Examples
Description
Function tests the main assumption of ordinary least squares (OLS), including
non-multicollinearity, non-autocorrelation and homoskedasticity.
Usage
1
testDiagnostics(model, alpha = 0.05)
Arguments
model
Linear model to test.
alpha
Critical value of hypothesis tests.
Value
Named vector with outcomes of main test statistics.
Examples
1
2
3
4
library(car)
m <- lm(mpg ~ disp + hp + wt + drat, data = mtcars)
testDiagnostics(m)
sfeuerriegel/ResearchGroupTools documentation built on May 29, 2019, 8:01 p.m.
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Description Usage Arguments Value Examples
Description
Function tests the main assumption of ordinary least squares (OLS), including non-multicollinearity, non-autocorrelation and homoskedasticity.
Usage
1 | testDiagnostics(model, alpha = 0.05)
|
Arguments
model |
Linear model to test. |
alpha |
Critical value of hypothesis tests. |
Value
Named vector with outcomes of main test statistics.
Examples
1 2 3 4 | library(car)
m <- lm(mpg ~ disp + hp + wt + drat, data = mtcars)
testDiagnostics(m)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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