morals: Multiple Regression (MORALS).

In Gifi: Multivariate Analysis with Optimal Scaling

Multiple Regression (MORALS).

Description

Fits multiple regression within the Gifi framework.

Usage

morals(x, y, xknots = knotsGifi(x, "Q"), yknots = knotsGifi(y, "Q"), xdegrees = 2, 
ydegrees = 2, xordinal = TRUE, yordinal = TRUE, xties = "s", yties = "s", xmissing = "m", 
ymissing = "m", xactive = TRUE, xcopies = 1, itmax = 1000, eps = 1e-6, verbose = FALSE)

Arguments

x	Vector or data frame with predictor variables (all numeric)
y	Vector with response variable
xknots	Knots specification for predictors (see knotsGifi)
yknots	Knots specification for response (see knotsGifi)
xdegrees	Degree specification for predictors
ydegrees	Degree specification for response
xordinal	Whether predictors should be considered as ordinal or not. Alternatively, one can specify a boolean vector of length m denoting which variables should be ordinally restricted or not
yordinal	Whether response should be considered as ordinal or not
xties	How predictor ties should be handled: primary ("p"), secondary ("s"), or tertiary ("t")
yties	How response ties should be handled: primary ("p"), secondary ("s"), or tertiary ("t")
xmissing	How missing predictor values should be handled: multiple ("m"), single ("s"), or average ("a")
ymissing	How missing response values should be handled: multiple ("m"), single ("s"), or average ("a")
xactive	Which predictors should be active or inactive
xcopies	Number of copies for each predictor
itmax	Maximum number of iterations
eps	Convergence criterion
verbose	Iteration printout

Details

Fits MORALS as described in De Leeuw et al. (2017).

Value

rhat	Induced correlation matrix
objectscores	Object scores (rows)
xhat	Optimally transformed predictors
yhat	Optimally transformed response
ypred	Predicted (fitted) values
yres	Residuals
smc	Squared multiple correlation
ntel	Number of iterations
f	Loss function value

References

Gifi, A. (1990). Nonlinear Multivariate Analysis. New York: Wiley.

De Leeuw, J., Mair, P., Groenen, P. J. F. (2017). Multivariate Analysis with Optimal Scaling.

See Also

homals, princals, plot.morals

Examples

x <- scale(as.matrix(seq(0, pi, length = 20)), scale = FALSE)
y <- scale(as.matrix(sin(x)), scale = FALSE)
fitxy <- morals(x, y, xknots = knotsGifi(x, "E"), xdegrees = 2)
plot(fitxy, main = c("x", "y"))
plot(fitxy, plot.type = "resplot")

plot(fitxy$xhat, fitxy$yhat)
lines(fitxy$xhat, fitxy$ypred)

plot(x, fitxy$yhat)
lines(x, fitxy$ypred)

Gifi documentation built on Sept. 28, 2022, 3 a.m.