gendata_Fac

Generate simulated data from high dimensional sparse factor model.

factor

feature

A general framework of two directional simultaneous inference
is provided for high-dimensional as well as the fixed dimensional models with manifest
variable or latent variable structure, such as high-dimensional mean models, high-
dimensional sparse regression models, and high-dimensional latent factors models.
It is making the simultaneous inference on a set of parameters from two directions,
one is testing whether the estimated zero parameters indeed are zero and the other is
testing whether there exists zero in the parameter set of non-zero. More details can be
referred to Wei Liu, et al. (2022) <doi:10.48550/arXiv.2012.11100>.

Wei Liu

TOSI

Two-Directional Simultaneous Inference for High-Dimensional
Models

Huazhen Lin

gendata_Fac function

<dl> <dt>n</dt>
<dd>a positive integer, the sample size.</dd> <dt>p</dt>
<dd>an positive integer, the variable dimension.</dd> <dt>seed</dt>
<dd>a nonnegative integer, the random seed, default as 1.</dd> <dt>q</dt>
<dd>a positive integer, the number of factors.</dd> <dt>pzero</dt>
<dd>a positive integer, the number of zero loading vectors, default as p/4.</dd> <dt>sigma2</dt>
<dd>a positive real number, the homogenous variance of error term.</dd> <dt>gamma</dt>
<dd>a positive number, the common component of heteroscedasticity of error term.</dd> <dt>heter</dt>
<dd>a logical value, indicates whether generate heteroscendastic error term.</dd> <dt>rho</dt>
<dd>a positive number, controlling the magnitude of loading matrix.</dd></dl>

Arguments

Author

Generate simulated data — gendata_Fac

<dl>

 <dt>n</dt>
<dd>a positive integer, the sample size.</dd>

 <dt>p</dt>
<dd>an positive integer, the variable dimension.</dd>

 <dt>seed</dt>
<dd>a nonnegative integer, the random seed, default as 1.</dd>

 <dt>q</dt>
<dd>a positive integer, the number of factors.</dd>

 <dt>pzero</dt>
<dd>a positive integer, the number of zero loading vectors, default as p/4.</dd>

 <dt>sigma2</dt>
<dd>a positive real number, the homogenous variance of error term.</dd>

 <dt>gamma</dt>
<dd>a positive number, the common component of heteroscedasticity of error term.</dd>

 <dt>heter</dt>
<dd>a logical value, indicates whether generate heteroscendastic error term.</dd>

 <dt>rho</dt>
<dd>a positive number, controlling the magnitude of loading matrix.</dd>

</dl>

gendata_Fac: Generate simulated data

Description

Usage

Value

Arguments

Author

See Also

Examples