我有一个问题，关于如何获得nlme中随机效应系数的不确定性值。
我建立了一个数据集，以了解不同位置施肥对谷物产量的响应（农艺实验）。该模型是二次平稳模型。模型参数是最大产量（Ymax），最大产量的施肥（M）和初始斜率（k）。对于给定的位置，M为202.4，Ymax为14306.79。我想以不确定性的方式报告这些系数。我如何获得标准差的值或这些系数？
这是一个可复制的示例。
library(nlme)
#dataframe
loc <- c("Loc1", "Loc2", "Loc3")
block <- c("Block_1", "Block_2", "Block_3", "Block_4")
treat <- as.numeric(c("0","40","80","120","160","200","240","280"))
empty <-expand.grid(treat, block, loc)
response <- as.numeric(c(7064, 9250, 12306, 13549, 13300, 13973,
14749, 14086, 7680, 11426, 12874, 12556, 14274, 14289, 15295, 14587,
8445, 11588, 13223, 13322, 13508, 13616, 13747, 13352,
9454, 11104, 12462, 13373, 14060, 14576, 14133, 14427,
5463, 8689, 10194, 11996, 13475, 12544, 12856, 11557,
5251, 7537, 12074, 12438, 12120, 11312, 9908, 12841,
4643, 7513, 10499, 12423, 12177, 12545, 12876, 13047,
4992, 9458, 11071, 12104, 13552, 12602, 13210, 14428,
4061, 3959, 5871, 8016, 9472, 11554, 12525, 12636,
4598, 7717, 7274, 8476, 9433, 10768, 10275, 8200,
4862, 5727, 6468, 8532, 10662, 12054, 12227, 12672,
5218, 7878, 8238, 10303, 10331, 13337, 12877, 11661))
resp.data <- cbind(empty, response)
resp.data <- resp.data[c("Var3", "Var2", "Var1", "response")]
names(resp.data) <- c("loc", "block", "treat", "response")
f.quad.loc <- nlme(response ~ ymax*(treat > M) +
(ymax - (k/2) * (M-treat)^2) * (treat < M),
data = resp.data,
fixed = list(ymax ~ 1,
M ~ 1,
k ~ 1),
random = list(loc = pdDiag(ymax + M + k ~ 1)),
start = c(12000,
100,
0.2),
na.action = na.omit,
verbose = F)
r.effects <- random.effects(f.quad.loc)
f.effects <- fixed.effects(f.quad.loc)
r.effects$ymax <- r.effects$ymax + f.effects[1]
r.effects$M <- r.effects$M + f.effects[2]
r.effects$k <- r.effects$k+ f.effects[3]
r.effects
非常感谢。