大家好，我今天看了一篇“介绍如何对PLS最小样本量和统计检定力计算”的文章，Aguirre-Urreta, M., & Rönkkö, M. (2015). Sample size determination and statistical power analysis in PLS using r: An annotated tutorial. Communications of the Association for Information Systems, 36(1), 33-51.
      在该文中，作者提供了一串代码用以实现上述目的，代码如下：

library(matrixpls)

model<-"! regressions
A=~0.7*x1
A=~0.7*x2
A=~0.7*x3
B=~0.7*x4
B=~0.7*x5
B=~0.8*x6
B=~0.8*x7
C=~0.6*x8
C=~0.6*x9
C=~0.6*x10
C=~0.8*x11
C=~0.8*x12
D=~0.8*x13
D=~0.8*x14
D=~0.8*x15
D ~ 0.3*A
C ~ 0.1*B
C ~ 0.5*A
D ~ 0.3*C
! residuals, variances and covariances
A ~~ 1.0*A
B ~~ 1.0*B
C ~~ 0.71*C
D ~~ 0.725*D
B ~~ 0.3*A
x1 ~~ 0.51*x1
x2 ~~ 0.51*x2
x3 ~~ 0.51*x3
x4 ~~ 0.51*x4
x5 ~~ 0.51*x5
x6 ~~ 0.36*x6
x7 ~~ 0.36*x7
x8 ~~ 0.64*x8
x9 ~~ 0.64*x9
x10 ~~ 0.64*x10
x11 ~~ 0.36*x11
x12 ~~ 0.36*x12
x13 ~~ 0.36*x13
x14 ~~ 0.36*x14
x15 ~~ 0.36*x15"

# Normal data

output <- matrixpls.sim(1000, model, n=100, multicore = TRUE, completeRep = TRUE)

summary(output)

        然后，该文提供的运行结果是：


但是我却无法得到上述结果，我的控制台所显示的所有内容为：
> library(matrixpls)

载入程辑包：‘matrixpls’

The following object is masked from ‘package:stats’:

    loadings
>
> model<-"! regressions
+ A=~0.7*x1
+ A=~0.7*x2
+ A=~0.7*x3
+ B=~0.7*x4
+ B=~0.7*x5
+ B=~0.8*x6
+ B=~0.8*x7
+ C=~0.6*x8
+ C=~0.6*x9
+ C=~0.6*x10
+ C=~0.8*x11
+ C=~0.8*x12
+ D=~0.8*x13
+ D=~0.8*x14
+ D=~0.8*x15
+ D ~ 0.3*A
+ C ~ 0.1*B
+ C ~ 0.5*A
+ D ~ 0.3*C
+ ! residuals, variances and covariances
+ A ~~ 1.0*A
+ B ~~ 1.0*B
+ C ~~ 0.71*C
+ D ~~ 0.725*D
+ B ~~ 0.3*A
+ x1 ~~ 0.51*x1
+ x2 ~~ 0.51*x2
+ x3 ~~ 0.51*x3
+ x4 ~~ 0.51*x4
+ x5 ~~ 0.51*x5
+ x6 ~~ 0.36*x6
+ x7 ~~ 0.36*x7
+ x8 ~~ 0.64*x8
+ x9 ~~ 0.64*x9
+ x10 ~~ 0.64*x10
+ x11 ~~ 0.36*x11
+ x12 ~~ 0.36*x12
+ x13 ~~ 0.36*x13
+ x14 ~~ 0.36*x14
+ x15 ~~ 0.36*x15"
>
> # Normal data
>
> output <- matrixpls.sim(1000, model, n=100, multicore = TRUE, completeRep = TRUE)
Progress tracker is not available when 'multicore' is TRUE.
>
> summary(output)
   Length     Class      Mode
        1 SimResult        S4

由于我很少用R语言，无法找出其中的问题，各位高手可否告知一二？谢谢。