如何修复mlogit错误：“系统在计算上是单个的：倒数条件编号”

Question

当我尝试将Ordered Logit模型拟合到较长的数据集时，这些函数将返回错误Error in solve.default(H, g[!fixed]): system is computationally singular: reciprocal condition number = 3.64628e-18。

我见过this，但是数据不再可用，因此无法解决问题。另外，尝试this one和this one失败。

复制我正在使用的数据集的代码是：

# Example of caracteristic dummies
caract <- tibble::tribble(~CPU, ~RAM,
                     1,    1,
                    -1,    1,
                     1,   -1,
                    -1,   -1)


# Weights for choosing the probabilities
weights <- c(0.3954545, 0.2727273, 0.2363636, 0.0954546)

# Simulating the choices block
block <- caract
block$Alternative <- 1:4

# Simulating the dataset
df <- NULL
n_decisors <- 50
set.seed(123456)
i <- 1
for(i in 1:n_decisors){
  block$Decisor <- i
  block$Choice <- sample(1:4, prob = weights)
  df <- rbind(df, block)
}

返回错误的模型拟合过程为：

library(mlogit)
# Creating the model data object
df_mlogit <- mlogit.data(data = df, choice = "Choice", 
                         shape = "long", alt.var = "Alternative", 
                         varying = 1:2, ranked = T)

# Fitting the model
m <- mlogit(formula = Choice ~ CPU + RAM, 
            rpar = c(CPU = "n", RAM = "n"), 
            data = df_mlogit)

当通过在caract模拟的每次迭代中对df的行进行采样来使选择块不完全时，不会发生错误，但是我需要估计一种情况，即该格式在此示例中进行模拟。另外，我知道nnet::multinom(Choice ~ CPU + RAM, data=df)解决了这个问题，但它不适合混合logit模型，这对我来说也是必需的。