R glmnet标准化的不同结果=错误

我正在运行

glmnet

，并尝试在使用

standarized=FALSE

预标准化变量时查看差异

library(glmnet)
data(QuickStartExample)
### Standardized Way
x_standardized <- scale(x, center = TRUE, scale = TRUE)
y_standardized <- scale(y, center = TRUE, scale = TRUE)
cv_standardized <- cv.glmnet(x_standardized, y_standardized,
                             intercept = FALSE,
                             standardize = FALSE, standardize.response = FALSE)
destandardized_coef <- coef(cv_standardized)[-1] * sd(y) / apply(x, 2, sd)
destandardized_coef
mean(y) - sum(destandardized_coef * colMeans(x))

### Let glmnet Stanardize
cv_normal <- cv.glmnet(x, y)
coef(cv_normal, cv_normal$lambda.min) %>% as.numeric()

我的问题是，如何提取相同的结果，以及为什么目前的系数以这种方式不同

提前谢谢

             personal_standardize   glmnet_standardize
(Intercept)            0.1536661  0.14867414
V1                     1.3019575  1.33377821
V2                     .          .         
V3                     0.6422426  0.69787701
V4                     .          .         
V5                    -0.7892388 -0.83726751
V6                     0.4944794  0.54334327
V7                     .          0.02668633
V8                     0.2943189  0.33741131
V9                     .          .         
V10                    .          .         
V11                    0.1058440  0.17105029
V12                    .          .         
V13                    .          .         
V14                   -1.0402312 -1.07552680
V15                    .          .         
V16                    .          .         
V17                    .          .         
V18                    .          .         
V19                    .          .         
V20                   -0.9791172 -1.05278699