[英]mgcv GAM with betar
有谁知道如何从模型输出(具有beta分布的mgcv GAM)中获取拟合的phi参数?
参考提供的betar gam示例 :
library(mgcv)
## Simulate some beta data...
set.seed(3);n<-400
dat <- gamSim(1,n=n)
mu <- binomial()$linkinv(dat$f/4-2)
phi <- .5
a <- mu*phi;b <- phi - a;
dat$y <- rbeta(n,a,b)
bm <- gam(y~s(x0)+s(x1)+s(x2)+s(x3),family=betar(link="logit"),data=dat)
输出显示“ Family:Beta回归”下的phi估计值
> bm
Family: Beta regression(0.491)
Link function: logit
Formula:
y ~ s(x0) + s(x1) + s(x2) + s(x3)
Estimated degrees of freedom:
1.73 1.63 5.62 1.00 total = 10.98
在拟合过程中,gam函数调用betar(),该函数随后估计称为theta的phi参数。 我引用了以下功能的说明:
描述:
Family for use with 'gam' or 'bam', implementing regression for beta distributed data on (0,1). A linear predictor controls the mean, mu of the beta distribution, while the variance is then mu(1-mu)/(1+phi), with parameter phi being estimated during fitting, alongside the smoothing parameters.
用法:
betar(theta = NULL, link = "logit",eps=.Machine$double.eps*100) Arguments: theta: the extra parameter (phi above).
使用您已有的示例,您只需要查看gam对象下方:
bm <- gam(y~s(x0)+s(x1)+s(x2)+s(x3),family=betar(link="logit"),data=dat)
exp(bm$family$getTheta())
[1] 0.4913482
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