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为什么在“gam(y~mgcv::s…”)中使用“mgcv::s”会导致错误?

mgcv syntax r

Manuel Bickel · 技术社区 · 6 年前

:: 用于拟合的行中的符号 mgcv::gam mgcv::s

原因可能是因为我在模型公式中使用了这个符号,但我无法理解为什么这不起作用/不被允许。这可能是关于语法的一些非常具体的东西(我想可能不是特定于mgcv),但也许有人可以帮助我理解这一点和我对r的理解。提前谢谢。

library(mgcv)
dat <- data.frame(x = 1:10, y = 101:110)
# this results in an error: invalid type (list)...
mgcv::gam(y ~ mgcv::s(x, bs = "cs", k = -1), data = dat)
# after removing the mgcv:: in front of s everything works fine
mgcv::gam(y ~ s(x, bs = "cs", k = -1), data = dat)

# outside of the model call, both calls return the desired function
class(s)
# [1] "function"
class(mgcv::s)
# [1] "function"

2 回复 | 直到 6 年前

Zheyuan Li 6 年前

解释

library(mgcv)
#Loading required package: nlme
#This is mgcv 1.8-24. For overview type 'help("mgcv-package")'.

f1 <- ~ s(x, bs = 'cr', k = -1)
f2 <- ~ mgcv::s(x, bs = 'cr', k = -1)

OK <- mgcv:::interpret.gam0(f1)$smooth.spec
FAIL <- mgcv:::interpret.gam0(f2)$smooth.spec

str(OK)
# $ :List of 10
#  ..$ term   : chr "x"
#  ..$ bs.dim : num -1
#  ..$ fixed  : logi FALSE
#  ..$ dim    : int 1
#  ..$ p.order: logi NA
#  ..$ by     : chr "NA"
#  ..$ label  : chr "s(x)"
#  ..$ xt     : NULL
#  ..$ id     : NULL
#  ..$ sp     : NULL
#  ..- attr(*, "class")= chr "cr.smooth.spec"

str(FAIL)
# list()

interpret.gam0

head(mgcv:::interpret.gam0)

1 function (gf, textra = NULL, extra.special = NULL)              
2 {                                                               
3     p.env <- environment(gf)                                    
4     tf <- terms.formula(gf, specials = c("s", "te", "ti", "t2", 
5         extra.special))                                         
6     terms <- attr(tf, "term.labels")

自 "mgcv::s" mgcv “mgcv::s” extra.special

FIX <- mgcv:::interpret.gam0(f, extra.special = "mgcv::s")$smooth.spec
all.equal(FIX, OK)
# [1] TRUE

head(mgcv::gam, n = 10)

#1  function (formula, family = gaussian(), data = list(), weights = NULL, 
#2      subset = NULL, na.action, offset = NULL, method = "GCV.Cp",        
#3      optimizer = c("outer", "newton"), control = list(), scale = 0,     
#4      select = FALSE, knots = NULL, sp = NULL, min.sp = NULL, H = NULL,  
#5      gamma = 1, fit = TRUE, paraPen = NULL, G = NULL, in.out = NULL,    
#6      drop.unused.levels = TRUE, drop.intercept = NULL, ...)             
#7  {                                                                      
#8      control <- do.call("gam.control", control)                         
#9      if (is.null(G)) {                                                  
#10         gp <- interpret.gam(formula)  ## <- default to extra.special = NULL

我同意本·博克的观点。这是一个很好的练习去挖掘里面发生的事情,但是把它当作一个bug并修复它是一种过度反应。

s ,请 te 不适用于同一逻辑 stats::poly splines::bs .

X <- splines::bs(x, df = 10, degree = 3) x X
当你这样做的时候 s(x, bs = 'cr', k = 10) .

MGCV公司

mgcv::interpret.gam
mgcv::smooth.construct 建立基础/设计矩阵和惩罚矩阵(主要在C级完成);
mgcv::smoothCon ,它选取“by”变量(例如,对于“by”因子复制平滑),线性函数项,空空间惩罚(如果使用 select = TRUE
最终整合 mgcv:::gam.setup

user2554330 6 年前

mgcv 问题。例如, lm() poly() stats::poly()

> x <- 1:100
> y <- rnorm(100)
> lm(y ~ poly(x, 3))

Call:
lm(formula = y ~ poly(x, 3))

Coefficients:
(Intercept)  poly(x, 3)1  poly(x, 3)2  poly(x, 3)3  
    0.07074      0.13631     -1.52845     -0.93285  

> lm(y ~ stats::poly(x, 3))

Call:
lm(formula = y ~ stats::poly(x, 3))

Coefficients:
       (Intercept)  stats::poly(x, 3)1  stats::poly(x, 3)2  stats::poly(x, 3)3  
           0.07074             0.13631            -1.52845            -0.93285

它也适用于 splines::bs

你应该联系 s mgcv::s