Library: | metrics |
See also: | dpls makedesign |
Quantlet: | redun | |
Description: | calculates a single redundance and a redundance vector for dpls quantlet as a measure of goodness. |
Usage: | {red,redm}=redun(b,sk,lk,skl,y) | |
Input: | ||
b | a matrix with loadings | |
sk | a matrix with path coefficients | |
lk | a matrix with latent variables | |
skl | a matrix with lagged path coefficients | |
y | a matrix with manifest variables (indicators) | |
Output: | ||
red | a scalar with single redundance value | |
redm | a vector with redundace values |
randomize(13409) library("metrics") b1=0.3 c1=0.6 s=500 n1=normal(s+1) n1lag=n1[1:s,] n1=n1[2:rows(n1),] ;innermodel n2=b1*n1+c1*n1lag+normal(rows(n1))/5 n=n1~n2 nn=n./sqrt(var(n)) ;loadingsmatrix p=(1|2|3|4|0|0|0)~(0|0|0|0|5|6|7) y=nn*p'+normal(rows(n),rows(p))/8 d=(0|1)~(0|0) dl=(0|1)~(0|0) w=(1|1|1|1|0|0|0)~(0|0|0|0|1|1|1) myfit=dpls(w,d,w,dl,y,1,3) {red,redm}=redun(myfit.b,myfit.sk,myfit.lk,myfit.skl,y) red redm
Contents of red [1,] 0.90498 Contents of redm [1,] 0 [2,] 0 [3,] 0 [4,] 0 [5,] 0.90491 [6,] 0.90489 [7,] 0.90515