Estimation of the Student-t Distribution

Performs maximum likelihood estimation on the Student-t distribution (univariate and multivariate). Wrappers fit.tuv and fit.tmv.

fit_t(x, symmetric = FALSE)

# S3 method for default
fit_t(x, symmetric = FALSE)

# S3 method for tbl
fit_t(x, symmetric = FALSE)

# S3 method for xts
fit_t(x, symmetric = FALSE)

# S3 method for matrix
fit_t(x, symmetric = FALSE)

Arguments

x	A tabular (non-tidy) data structure.
symmetric	A logical flag. Should the estimated distribution be symmetric? Defaults to FALSE.

Value

A list of the the class cma_fit with 21 components.

See also

fit_ghd fit_hyp fit_nig fit_vg fit_normal

Examples

x <- matrix(diff(log(EuStockMarkets)), ncol = 4)

# multivariate estimation
fit_t(x)
#> # Margins Estimation
#> Converged:       TRUE
#> Dimension:       4
#> AIC:            -52711.16
#> Log-Likelihood:  26374.58
#> Model:           Asymmetric Student-t

# univariate estimation
fit_t(x[ , 4, drop = FALSE])
#> # Margins Estimation
#> Converged:       TRUE
#> Dimension:       1
#> AIC:            -12791.05
#> Log-Likelihood:  6399.524
#> Model:           Asymmetric Student-t