spaMM: summary.HL – R documentation

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summary.HL

Summary and print methods for fit and test results.

Description

Summary and print methods for results from HLfit or related functions. summary may also be used as an extractor (see e.g. beta_table).

Usage

## S3 method for class 'HLfit'
summary(object, details=FALSE, max.print=100L, verbose=TRUE, ...)
## S3 method for class 'HLfitlist'
summary(object, ...)
## S3 method for class 'fixedLRT'
summary(object, verbose=TRUE, ...)
## S3 method for class 'HLfit'
print(x,...)
## S3 method for class 'HLfitlist'
print(x,...)
## S3 method for class 'fixedLRT'
print(x,...)

Arguments

`object`	An object of class `HLfit`, as returned by the fitting functions in `spaMM`.
`x`	The return object of HLfit or related functions.
`verbose`	For `summary.HLfit`, whether to print the screen output that is the primary purpose of summary. `verbose=FALSE` may be convenient when `summary` is used as an extractor. For `summary.fixedLRT`, whether to print the model fits or not.
`max.print`	Controls `options("max.print")` locally.
`details`	A vector with elements controlling whether to print some obscure details. Element `ranCoefs=TRUE` will print details about random-coefficients terms (see Details); and element `p_value="Wald"` will print a p-value for the t-value of each fixed-effect coefficient, assuming a gaussian distribution of the test statistic (but, beyond the generally questionable nature of p-value tables, see e.g. `LRT` and `fixedLRT` for alternative testing approaches).
`...`	further arguments passed to or from other methods.

Details

The random effect terms of the linear predictor are of the form ZLv. In particular, for random-coefficients models (i.e., including random-effect terms such as (z|group) specifying a random-slope component), correlated random effects are represented as b = Lv for some matrix L, and where the elements of v are uncorrelated. In the output of the fit, the Var. column gives the variances of the correlated effects, b=Lv. The Corr. column(s) give their correlation(s). If details is TRUE, estimates and SEs of the (log) variances of the elements of v are reported as for other random effects in the Estimate and cond.SE. columns of the table of lambda coefficients. However, this non-default output is potentially misleading as the elements of v cannot generally be assigned to specific terms (such as intercept and slope) of the random-effect formula, and the representation of b as Lv is not unique.

Value

These methods return the object invisibly. They print details of the fits in a convenient form.

Examples

## see examples of fitme() or corrHLfit() usage

spaMM

Mixed-Effect Models, with or without Spatial Random Effects

v3.10.0

CeCILL-2

Authors

François Rousset [aut, cre, cph] (<https://orcid.org/0000-0003-4670-0371>), Jean-Baptiste Ferdy [aut, cph], Alexandre Courtiol [aut] (<https://orcid.org/0000-0003-0637-2959>), GSL authors [ctb] (src/gsl_bessel.*)

Initial release

2022-02-06