问对rms软件包中安装的ols模型使用校准功能时出错

EN

> library(rms)
> library(MASS)
> data(whiteside)
> w.Before <- whiteside[whiteside$Insul=="Before",]
# For comparability with an example in MASS.
> dd <- datadist(w.Before)
> options(datadist="dd")

> mod1 <- ols(Gas ~ Temp,data=w.Before,
                         x=TRUE,y=TRUE)
> mod1
            Coef    S.E.   t      Pr(>|t|)
 Intercept  6.8538 0.1184  57.88 <0.0001 
 Temp      -0.3932 0.0196 -20.08 <0.0001

# ols() estimates the coefficients correctly

# Five-fold cross-validation for this model fit:
> validate(mod1,bw=FALSE,method="crossvalidation",B=5)
           index.orig training    test optimism index.corrected n
 R-square      0.9438   0.9431  0.8460   0.0971          0.8467 5
 MSE           0.0731   0.0709  0.0929  -0.0220          0.0951 5
 g             1.2791   1.2664  1.2222   0.0442          1.2349 5
 Intercept     0.0000   0.0000 -0.1661   0.1661         -0.1661 5
 Slope         1.0000   1.0000  1.0360  -0.0360          1.0360 5

# try using default argument options:
> calibrate(mod1)
Error in !fail : invalid argument type

# try using some arguments specific to the fitted ols object:
> calibrate(mod1,predy=median(w.Before$Gas),method="crossvalidation",B=5)
Error in !fail : invalid argument type

mod1 <- ols(Gas ~ Temp,data=w.Before,
                         x=TRUE,y=TRUE)

# Switch on debug argument:
> calibrate(mod1, debug = TRUE)

Subscripts of training sample:
 [1]  3  9 15 22 21  4  7 22  8  5 11 10 25  4 10  5 18 23  6  1 19 10  9  6 22 25

Subscripts of test sample:
 [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

Error in !fail : invalid argument type
> traceback()
3: predab.resample(fit, method = method, fit = fitit, measure = cal.error, 
   pr = pr, B = B, bw = bw, rule = rule, type = type, sls = sls, 
   aics = aics, force = force, estimates = estimates, non.slopes.in.x = 
model == 
       "ol", smoother = smoother, predy = predy, model = model, 
   kint = kint, penalty.matrix = penalty.matrix, ...)
2: calibrate.default(mod1, debug = TRUE)
1: calibrate(mod1, debug = TRUE)

> options(error = recover)
> calibrate(mod1)
Error in !fail : invalid argument type

Enter a frame number, or 0 to exit   

1: calibrate(mod1)
2: calibrate.default(mod1)
3: predab.resample(fit, method = method, fit = fitit, measure = cal.error, pr = p

Selection: 3
Called from: calibrate.default(mod1)

# Entering object names in predab.resample function from last object in this function until I find an error / missing or suspect values:
Browse[1]> res                      
Error during wrapup: object 'res' not found

Browse[1]> varin                                                            
Error during wrapup: object 'varin' not found

Browse[1]> index.orig
 [1] -0.0146323 -0.0095743 -0.0052462 -0.0023136  0.0004922  0.0032980  0.0061038
 [8]  0.0081017  0.0111468  0.0147536  0.0183605  0.0219674  0.0255743  0.0291812
 [15]  0.0346582  0.0427575  0.0513092  0.0584638  0.0626379  0.0668120  0.0709861
 [22]  0.0751603  0.0793344  0.0832308  0.0830547  0.0828785  0.0827024  0.08 25263
 [29]  0.0823502  0.0821740  0.0819979  0.0818218  0.0816456  0.0814695  0.0812934
 [36]  0.0820341  0.0833151  0.0845299  0.0857447  0.0858007  0.0842924  0.0827842
 [43]  0.0801835  0.0750078  0.0698321  0.0646565  0.0591428  0.0513195  0.0434962
 [50]  0.0356728
attr(,"keepinfo")
attr(,"keepinfo")$orig.cal
 [1] 3.851 3.893 3.935 3.976 4.017 4.057 4.098 4.137 4.178 4.219 4.261 4.302 4.343
 [14] 4.385 4.428 4.474 4.520 4.565 4.607 4.649 4.691 4.732 4.774 4.816 4.854 4.891
 [27] 4.929 4.966 5.004 5.041 5.079 5.116 5.154 5.191 5.229 5.267 5.306 5.345 5.384
[40] 5.422 5.458 5.494 5.530 5.562 5.595 5.627 5.659 5.689 5.719 5.749

Browse[1]> optimism      
Error during wrapup: object 'optimism' not found