| Library: | gam |
| See also: | intestpl gintest gintestpl pcad gamfit |
| Quantlet: | intest | |
| Description: | estimation of the univariate additive functions in a separable additive model using Nadaraya-Watson, local linear or local quadratic estimation. |
| Usage: | gest = intest(t,y,h,g,loc{,opt}) | |
| Input: | ||
| t | n x p matrix, the observed explanatory variable where the directions of interest must be the first p columns. | |
| y | n x q matrix, the observed response variables. | |
| h | p(pg) x 1 matrix or scalar, chosen bandwidth for the directions of interest. | |
| g | p x 1 matrix or scalar, chosen bandwidth for the directions not of interest. | |
| loc | integer, it can take values 0, 1 or 2. For loc=0 local constant (Nadaraya-Watson), for loc=1 local linear and for loc=2 local quadratic estimator will be used. | |
| opt | list, composed of the following optional objects: | |
| opt.tg | ng x pg vector, a grid for continuous part. If tg is given, the nonparametric function will be computed on this grid. Default = t. | |
| opt.shf | integer, (show-how-far) if set to 1, an output is produced which indicates how the iteration is going on (additive function / point of estimation / number of iteration). Default = 0. | |
| Output: | ||
| gest | n(ng) x pp x q array, containing the marginal integration estimates of the additive components in the first p columns, the derivatives in the followings, so pp = pg*(loc+1). | |
library("gam")
randomize(0)
t = uniform(50,2)*2-1
g1 = 2*t[,1]
g2 = t[,2]^2
g2 = g2 - mean(g2)
y = g1 + g2 + normal(50,1) * sqrt(0.25)
h = #(1.2, 1.0)
g = #(1.4, 1.2)
loc = 1
gest = intest(t,y,h,g,loc)
gest
bild = createdisplay(1,2)
dat11 = t[,1]~g1
dat12 = t[,1]~gest[,1]
dat21 = t[,2]~g2
dat22 = t[,2]~gest[,2]
setmaskp(dat12,4,4,8)
setmaskp(dat22,4,4,8)
show(bild,1,1,dat11,dat12)
show(bild,1,2,dat21,dat22)
The marginal integration estimates of the additive functions and its derivatives, using local polynomials, see Severance-Lossin & Sperlich (1999). Plots of the additive funtions (black circles - true function, red triangles - estimated function) are displayed.