[英]How to declare the exponential distribution in gam() in mgcv in R
I have a small dataset derived from an experiment and I want to fit a gam model prescribing the distribution of Y to be exponential with rate 0.5.我有一个来自实验的小数据集,我想拟合一个 gam 模型,该模型规定 Y 的分布以 0.5 的指数呈指数分布。
My data is:我的数据是:
x1 x2 y
-1.000000 -1.000000 40
1.000000 -1.000000 5
-1.000000 1.000000 14
1.000000 1.000000 10
-1.414214 0.000000 35
1.414214 0.000000 7
0.000000 -1.414214 18
0.000000 1.414214 9
0.000000 0.000000 7
0.000000 0.000000 4
0.000000 0.000000 0
0.000000 0.000000 2
I have tried different way to pass to the gam function the type of the distribution but I always run into an exception.我尝试了不同的方式将分布类型传递给 gam 函数,但我总是遇到异常。 Eg,例如,
model.gam = gam(y ~ x1 * x2, family = exponential(rate=0.5), data = df)
Error in gam(y ~ x1 * x2, family = exponential(rate = 0.5), data = df): family not recognized
model.gam = gam(y ~ x1 * x2, family = exponential(), data = df)
Error in check_dims(rate, target_dim = dim): argument "rate" is missing, with no default
model.gam = gam(y ~ x1 * x2, family = exponential(), data = df, rate = 0.5)
Error in check_dims(rate, target_dim = dim): argument "rate" is missing, with no default
I don't think gam() supports this type of family.我不认为 gam() 支持这种类型的家庭。
You may want to consider gamlss() from the gamlss package instead in conjunction with the EXP distribution from the gamlss.dist package:您可能需要考虑 gamlss 包中的 gamlss() 而不是结合 gamlss.dist 包中的 EXP 分发:
https://www.rdocumentation.org/packages/gamlss/versions/5.0-6/topics/gamlss https://www.rdocumentation.org/packages/gamlss/versions/5.0-6/topics/gamlss
https://www.rdocumentation.org/packages/gamlss.dist/versions/5.0-4/topics/EXP https://www.rdocumentation.org/packages/gamlss.dist/versions/5.0-4/topics/EXP
Note that the EXP distribution has a mean, rather than rate, parameter.请注意,EXP 分布有一个均值参数,而不是比率参数。
See http://www.gamlss.com for details on the gamlss package.有关 gamlss 包的详细信息,请参阅http://www.gamlss.com 。
Also, for such a small data set, I doubt that you can accommodate an interaction term in your model - even fitting two main effects might be a bit of a stretch.此外,对于如此小的数据集,我怀疑您是否可以在您的模型中容纳交互项 - 即使拟合两个主要效应也可能有点牵强。
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