Description Usage Arguments Value References Examples

Performs a goodness-of-fit test of a linear model by testing whether the errors are independent of the covariates.

1 | ```
MINTregression(x, y, k, keps, w = FALSE, eps)
``` |

`x` |
The |

`y` |
The response vector of length |

`k` |
The value of |

`keps` |
The value of |

`w` |
The weight vector to be used for estimation of the joint entropy |

`eps` |
A vector of null errors which should have the same distribution as the errors are assumed to have in the linear model. |

The *p*-value corresponding the independence test carried out.

2017arXiv171106642BIndepTest

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
# Correctly specified linear model
x=runif(100,min=-1.5,max=1.5); y=x+rnorm(100)
plot(lm(y~x),which=1)
MINTregression(x,y,5,10,w=FALSE,rnorm(10000))
# Misspecified mean linear model
x=runif(100,min=-1.5,max=1.5); y=x^3+rnorm(100)
plot(lm(y~x),which=1)
MINTregression(x,y,5,10,w=FALSE,rnorm(10000))
# Heteroscedastic linear model
x=runif(100,min=-1.5,max=1.5); y=x+x*rnorm(100);
plot(lm(y~x),which=1)
MINTregression(x,y,5,10,w=FALSE,rnorm(10000))
# Multivariate misspecified mean linear model
x=matrix(runif(1500,min=-1.5,max=1.5),ncol=3)
y=x[,1]^3+0.3*x[,2]-0.3*x[,3]+rnorm(500)
plot(lm(y~x),which=1)
MINTregression(x,y,30,50,w=TRUE,rnorm(50000))
``` |

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