mklr: Error estimates of the regression coefficients
In SantanderMetGroup/climate4R.indices: Climate Index calculation for climate4R data
mklr R Documentation
Error estimates of the regression coefficients
Description
Univariate linear regression with error estimates for regression coefficients.
Usage
mklr(x, y)
Arguments
x
A vector of predictors.
y
A vector of observations.
Details
The mathematics behind the calculation of the error estimates of the
regression coefficients are based on the Dover's book by A.A.Sveshnikov
"Problems in Probability Theory,...", p.326, –AK, Feb 27 2004.
Performs univariate linear regression of y on x:
y = r0 + r1*x
Value
Returns a list with the estimates (coefficients: r0, r1,
and their standard errors: sig0 and sig1).
Author(s)
J. Baño-Medina, S. Herrera
SantanderMetGroup/climate4R.indices documentation built on July 3, 2023, 11:02 p.m.
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| mklr | R Documentation |
Error estimates of the regression coefficients
Description
Univariate linear regression with error estimates for regression coefficients.
Usage
mklr(x, y)
Arguments
x |
A vector of predictors. |
y |
A vector of observations. |
Details
The mathematics behind the calculation of the error estimates of the regression coefficients are based on the Dover's book by A.A.Sveshnikov "Problems in Probability Theory,...", p.326, –AK, Feb 27 2004. Performs univariate linear regression of y on x: y = r0 + r1*x
Value
Returns a list with the estimates (coefficients: r0, r1, and their standard errors: sig0 and sig1).
Author(s)
J. Baño-Medina, S. Herrera
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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