lmPIT: Compute probability inverse transform values for linear...
In gofedf: Goodness of Fit Tests Based on Empirical Distribution Functions
View source: R/utils_lmnormal.R
lmPIT R Documentation
Compute probability inverse transform values for linear models.
Description
Compute probability inverse transform values for linear models.
Usage
lmPIT(x, y, theta)
Arguments
x
a matrix with n rows and p columns containing the explanatory variables.
y
a numeric vector of length n containing the response variable.
theta
a numeric vector of length (p+1), containing MLE of parameters in a linear model.
Value
a vector of length n containing the probability inverse transformed (PIT) values
gofedf documentation built on Oct. 1, 2023, 5:08 p.m.
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View source: R/utils_lmnormal.R
| lmPIT | R Documentation |
Compute probability inverse transform values for linear models.
Description
Compute probability inverse transform values for linear models.
Usage
lmPIT(x, y, theta)
Arguments
x |
a matrix with n rows and p columns containing the explanatory variables. |
y |
a numeric vector of length n containing the response variable. |
theta |
a numeric vector of length (p+1), containing MLE of parameters in a linear model. |
Value
a vector of length n containing the probability inverse transformed (PIT) values
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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