meanU2: Compute Mean Square Latent Variables

In AIDA: Analysis of Interval DAta

Compute Mean Square Latent Variables

Description

Obtain the mean of the square of the latent variables inherent to the macrodata.

Usage

meanU2(
  LatentDist = c("Unif", "Triang", "TNorm", "InvTri", "Beta", "KDE", "Degenerated"),
  TriangParam = 0,
  BetaParam.a = 1,
  BetaParam.b = 1,
  Umicro = NULL,
  p = NULL
)

Arguments

LatentDist	A string or vector of strings specifying the distribution(s) of the latent variables. If the variables are identically distributed it can be one of ("Unif", "Triang", "TNorm", "InvTri", "Beta", "KDE", "Degenerated"), if not a vector must be provided with the distribution for each variable.
TriangParam	Mode of the triangular distribution. If the latent variables are identically distributed, it is only necessary to provide a number, if not a vector is needed. The default is 0.
BetaParam.a	Parameter alpha of the Beta distribution. If the latent variables are identically distributed, it is only necessary to provide a number, if not a vector is needed. The default is 1.
BetaParam.b	Parameter beta of the Beta distribution. If the latent variables are identically distributed, it is only necessary to provide a number, if not a vector is needed. The default is 1.
Umicro	Latent microdata observations. Needed if LatentDist="KDE".
p	Number of variables.

Value

Either a diagonal matrix with the mean of the square of each variable or a value if the variables are identically distributed.

AIDA documentation built on Nov. 4, 2026, 9:06 a.m.