select {fanc}

select from a "fanc" object for fixed value of gamma.

Description

This functions give us the loadings from a "fanc" object for fixed value of gamma.

Usage

select(x, criterion=c("BIC","AIC","CAIC","EBIC"), 
	gamma,  scores=FALSE, df.method="active")

Arguments

x

Fitted "fanc" model object.

criterion

The criterion by which to select the tuning parameter rho. One of "AIC", "BIC", "CAIC", or "EBIC". Default is "BIC".

gamma

The value of gamma.

scores

Logical flag for outputting the factor scores. Defalut is FALSE.

df.method

Two types of degrees of freedom are supported. If "active", the degrees of freedom of are the number of nonzero parameters. If "reparametrization", the degrees of freedom of the MC+ are reparametrized based on the degrees of freedom of the lasso.

Value

loadings

factor loadings

uniquenesses

unique variances

Phi

factor correlation

scores

factor scores

df

degrees of freedom (number of non-zero parameters for the lasso estimation)

criteria

values of AIC, BIC and CAIC

goodness.of.fit

values of GFI and AGFI

rho

a value of rho

gamma

a value of gamma

Author(s)

Kei Hirose
[e-mail]

References

Hirose, K. and Yamamoto, M. (2014). Sparse estimation via nonconcave penalized likelihood in a factor analysis model,
Statistics and Computing, in press

See Also

fanc and plot.fanc objects.