Factorm | R Documentation |

Factor analysis to extract latent linear factor and estimate loadings.

```
Factorm(X, q=NULL)
```

`X` |
a |

`q` |
an integer between 1 and |

return a list with class named `fac`

, including following components:

`hH` |
a |

`hB` |
a |

`q` |
an integer between 1 and |

`sigma2vec` |
a p-dimensional vector, the estimated variance for each error term in model. |

`propvar` |
a positive number between 0 and 1, the explained propotion of cummulative variance by the |

`egvalues` |
a n-dimensional(n<=p) or p-dimensional(p<n) vector, the eigenvalues of sample covariance matrix. |

nothing

Liu Wei

Fan, J., Xue, L., and Yao, J. (2017). Sufficient forecasting using factor models. Journal of Econometrics.

`gfm`

.

```
dat <- gendata(n = 300, p = 500)
res <- Factorm(dat$X)
measurefun(res$hH, dat$H0) # the smallest canonical correlation
```

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