使用bam（）with family = betar使用bam（）的游戏错误

Question

我在求解bam（）从MGCV运行bam（）时遇到的错误遇到了困难。

我注意到，报告了类似的错误在这里 14个月前，似乎没有达成共识 - 建议给西蒙·伍德发送电子邮件。

我的数据是在这里。数据集太大，无法粘贴dput（）的输出。

但是，如果我使用整个数据集运行以下模型，则会得到以下错误

library(mgcv)

m3 <- bam(pt10 ~ 
            org.type +
            region +
            s(year) + 
            s(year, by = org.type) +
            s(year, by = region), 
          data = error, 
          method = "fREML", 
          family = betar(link="logit", eps = 0.1),
          select = T)

Warning messages:
1: In estimate.theta(theta, family, G$y, linkinv(eta), scale = scale1,  :
  step failure in theta estimation
2: In wt * LS :
  longer object length is not a multiple of shorter object length
3: In muth * (log(y) - log1p(-y)) :
  longer object length is not a multiple of shorter object length
4: In -lgamma(theta) + lgamma(muth) + lgamma(theta - muth) - muth *  :
  longer object length is not a multiple of shorter object length
5: In -lgamma(theta) + lgamma(muth) + lgamma(theta - muth) - muth *  :
  longer object length is not a multiple of shorter object length
6: In -lgamma(theta) + lgamma(muth) + lgamma(theta - muth) - muth *  :
  longer object length is not a multiple of shorter object length
7: In prior. weights * y :
  longer object length is not a multiple of shorter object length
8: In 2 * wt * (-lgamma(theta) + lgamma(muth) + lgamma(theta - muth) -  :
  longer object length is not a multiple of shorter object length

，但是，如果我使用整个数据集运行相同的模型，但是我排除了最后一行，则该模型似乎可以运行

m3 <- bam(pt10 ~ 
            org.type +
            region +
            s(year) + 
            s(year, by = org.type) +
            s(year, by = region), 
          data = error[1:20500,], 
          method = "fREML", 
          family = betar(link="logit", eps = 0.1),
          select = T)

OK向我建议，数据集的最后一行有问题。但是，我在数据集的最后一行中看不到任何错误，我期望会产生上述警告消息。

如果我再次在数据的一小部分上运行相同的模型，但是这次包括最后一行数据，则该模型似乎可以运行正常。

m3 <- bam(pt10 ~ 
            org.type +
            region +
            s(year) + 
            s(year, by = org.type) +
            s(year, by = region), 
          data = error[20400:20501,], 
          method = "fREML", 
          family = betar(link="logit", eps = 0.1),
          select = T)

但是，更大的数据子集（包括最后一行）再次产生与上面的类似警告消息。

m3 <- bam(pt10 ~ 
            org.type +
            region +
            s(year) + 
            s(year, by = org.type) +
            s(year, by = region), 
          data = error[10000:20501,], 
          method = "fREML", 
          family = betar(link="logit", eps = 0.1),
          select = T)

Warning messages:
1: In wt * LS :
  longer object length is not a multiple of shorter object length
2: In muth * (log(y) - log1p(-y)) :
  longer object length is not a multiple of shorter object length
3: In -lgamma(theta) + lgamma(muth) + lgamma(theta - muth) - muth *  :
  longer object length is not a multiple of shorter object length
4: In -lgamma(theta) + lgamma(muth) + lgamma(theta - muth) - muth *  :
  longer object length is not a multiple of shorter object length
5: In -lgamma(theta) + lgamma(muth) + lgamma(theta - muth) - muth *  :
  longer object length is not a multiple of shorter object length
6: In prior.weights * y :
  longer object length is not a multiple of shorter object length
7: In 2 * wt * (-lgamma(theta) + lgamma(muth) + lgamma(theta - muth) -  :
  longer object length is not a multiple of shorter object length
8: In bgam.fit(G, mf, chunk.size, gp, scale, gamma, method = method,  :
  algorithm did not converge

任何建议都感谢。

Answer 1

我怀疑问题是您的EPS（这可能确实表明您对数据有问题）。

默认值为：

r
gt; .Machine$double.eps*100                                                     
[1] 2.220446e-14

因此，您将所有响应值截断为Interval [EPS，1-EPS]（即任何内容y＆lt; eps 或y＆gt; 1 -eps正在重置为EPS和1- EPS aidgeifice。）。我想这会导致拟合算法问题，并且正在遇到未预料到的情况。如果范围[EPS，1-eps] 的范围不超过数量的值数量并不重要，那么您将在该范围的范围内堆积所有这些值，我怀疑这会导致数据细微变化的情况会导致拟合算法中的数值问题。

与您一样，将数据截断表明这不是适合您的数据的正确分布。如果没有其他任何信息，我会在其他地方寻找一种更合适的方法。