Description Usage Arguments Value Note Author(s) References See Also Examples

Generate the covariates and the response for generalized linear models in simulation.

1 |

`n` |
the sample size. |

`p` |
the dimension of the covariates. |

`alpha` |
the coefficients in moving average model |

`norm` |
the norm of coefficient vector under the alternative hypothesis (norm of |

`no` |
the number of nonzero coefficients under the alternative hypothesis (do not account the number of nuisance parameter). The default is |

`betanui` |
the vector which denotes the value of the nuisance coefficients. The default is |

`model` |
a character string to describe the model. The default is |

An object of class "DGP" is a list containing the following components:

`X` |
the design matrix with |

`Y` |
the response with length |

The covariates *X[i]=(X[i1],X[i2],...,X[ip])* are generated by the moving average model

* X[ij]=α[1]Z[ij]+α[2]Z[i(j+1)]+...+α[T]Z[i(j+T-1)],*

where *Z[i]=(Z[i1],Z[i2],...,Z[i(p+T-1)])* were generated from the *p+T-1* dimensional standard normal distribution

Bin Guo

Guo, B. and Chen, S. X. (2015). Tests for High Dimensional Generalized Linear Models.

1 2 3 4 5 6 7 8 9 10 11 12 | ```
alpha=runif(5,min=0,max=1)
## Example 1: Linear model
## H_0: \beta_0=0
DGP_0=DGP(80,320,alpha)
## Example 2: Logistic model
## H_0: \beta_0=0
DGP_0=DGP(80,320,alpha,model="logistic")
## Example 3: Linear model with the first five coefficients to be nonzero,
## the square of the norm of the coefficients to be 0.2
DGP_0=DGP(80,320,alpha,sqrt(0.2),5)
``` |

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