| Library: | metrics |
| See also: | glm dpls makedesign |
| Quantlet: | redun | |
| Description: | calculating single redundance and redundance vector for dpls macro as measure for 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 | |
library("metrics")
randomize(13409)
b1=0.3
c1=0.6
s=500
n1=normal(s+1)
n1lag=n1[1:s,]
n1=n1[2:rows(n1),]
n2=b1*n1+c1*n1lag+normal(rows(n1))/5
n=n1 ~ n2
nn=n./sqrt(var(n))
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 )
{wg,b,sk,skl,lk,iter}=dpls(w,d,w,dl,y,3)
{red,redm}=redun(b,sk,lk,skl,y)
sk
skl
b
red
Contents of sk [1,] 0 0 [2,] 0.423 0 Contents of skl [1,] 0 0 [2,] 0.856 0 Contents of b [1,] 0.9967 0 [2,] 2.0131 0 [3,] 3.005 0 [4,] 4.0134 0 [5,] 0 5.0093 [6,] 0 5.9997 [7,] 0 6.9937 Contents of red [1,] 0.90498
| Library: | metrics |
| See also: | glm dpls makedesign |