强制不发生 R 会话在 RStudio 中中止

问：

我想为多个 GLMM 模型创建一个循环，但我知道某些因素无法拟合。我创建了一些参数来避免错误，例如 、 和最小点限制 （）。 尽管有所有这些步骤，我总是有，但我找不到任何方法可以忽略不太适合的因素。skip_to_next <- FALSEtryCatchif(length(unique(NEW_DS_F_pred_sub$DATE))>=4)R Session Aborted

在我的例子中：

library("glmmTMB")
library("dplyr")
library("ggeffects")
library("ggplot2")

NEW_DS_F_pred <- NULL
STAND <- c(rep("A",5),rep("B",3),rep("C",6),rep("D",4))
stands <- unique(STAND)
DATE <- c("2022-01-01","2022-02-12","2022-03-01","2022-04-05","2022-06-01",
"2022-01-01","2022-02-12","2022-03-01",
"2022-01-01","2022-02-12","2022-03-01","2022-04-05","2022-06-01","2022-06-20",
"2022-01-01","2022-02-12","2022-03-01","2022-04-05")
B2_MAX <- runif(n=length(DATE))
B3_MAX <- runif(n=length(DATE))
B4_MAX <- runif(n=length(DATE))
NEW_DS_F_pred <- cbind(STAND,DATE,B2_MAX,B3_MAX,B4_MAX) %>% as.data.frame()

for (i in 1:length(stands)){
        skip_to_next <- FALSE
        tryCatch(print(stands[i]), error = function(e) { skip_to_next <<- TRUE})

NEW_DS_F_pred_sub <- NEW_DS_F_pred%>%filter(STAND==stands[i])

if(length(unique(NEW_DS_F_pred_sub$DATE))>=4){

NEW_DS_F_pred_sub$DATE_TIME <- as.numeric(difftime(NEW_DS_F_pred_sub$DATE, as.Date("2022-06-30"), units = "days"))
NEW_DS_F_pred_sub$DATE_TIME <- as.numeric(NEW_DS_F_pred_sub$DATE_TIME)
NEW_DS_F_pred_sub$B2_MAX <- as.numeric(NEW_DS_F_pred_sub$B2_MAX)
NEW_DS_F_pred_sub$B3_MAX <- as.numeric(NEW_DS_F_pred_sub$B3_MAX)
NEW_DS_F_pred_sub$B4_MAX <- as.numeric(NEW_DS_F_pred_sub$B4_MAX)
NEW_DS_F_pred_sub<-as.data.frame(NEW_DS_F_pred_sub)

# Fit the model B2_MAX
glmm_fit_B2_MAX <- glmmTMB(B2_MAX ~ poly(DATE_TIME,3) + (1|DATE_TIME), data=NEW_DS_F_pred_sub, family=tweedie(link = "log"))
ggeffects::ggpredict(glmm_fit_B2_MAX, terms = "DATE_TIME [all]") %>% plot(add.data = TRUE) + 
  xlab('Time in days') +
  ylab('VI 1')

# Predict the values
glmm_fit_B2_MAX_new <- NULL
glmm_fit_B2_MAX_new$DATE_TIME <- seq(-180,1)
glmm_fit_B2_MAX_new$B2_MAX <- predict(
  glmm_fit_B2_MAX,
  newdata = glmm_fit_B2_MAX_new,
  type = c("response"))
glmm_fit_B2_MAX_new$STAND <- rep(stands[i], length(glmm_fit_B2_MAX_new$DATE_TIME)) 
glmm_fit_B2_MAX_new <- as.data.frame(glmm_fit_B2_MAX_new)
glmm_fit_B2_MAX_new <- glmm_fit_B2_MAX_new%>%dplyr::select(STAND,DATE_TIME,B2_MAX)

# Fit the model B3_MAX
glmm_fit_B3_MAX <- glmmTMB(B3_MAX ~ poly(DATE_TIME,3) + (1|DATE_TIME), data=NEW_DS_F_pred_sub, family=tweedie(link = "log"))

# Predict the values
glmm_fit_B3_MAX_new <- NULL
glmm_fit_B3_MAX_new$DATE_TIME <- seq(-180,1)
glmm_fit_B3_MAX_new$B3_MAX <- predict(
  glmm_fit_B3_MAX,
  newdata = glmm_fit_B3_MAX_new,
  type = c("response"))
glmm_fit_B3_MAX_new$STAND <- rep(stands[i], length(glmm_fit_B3_MAX_new$DATE_TIME)) 
glmm_fit_B3_MAX_new <- as.data.frame(glmm_fit_B3_MAX_new)

# Fit the model B4_MAX
glmm_fit_B4_MAX <- glmmTMB(B4_MAX ~ poly(DATE_TIME,3) + (1|DATE_TIME), data=NEW_DS_F_pred_sub, family=tweedie(link = "log"))

# Predict the values
glmm_fit_B4_MAX_new <- NULL
glmm_fit_B4_MAX_new$DATE_TIME <- seq(-180,1)
glmm_fit_B4_MAX_new$B4_MAX <- predict(
  glmm_fit_B4_MAX,
  newdata = glmm_fit_B4_MAX_new,
  type = c("response"))
glmm_fit_B4_MAX_new$STAND <- rep(stands[i], length(glmm_fit_B4_MAX_new$DATE_TIME)) 
glmm_fit_B4_MAX_new <- as.data.frame(glmm_fit_B4_MAX_new)

if(skip_to_next) { next }     
}
}
#
#

有没有办法在不中止 R 会话的情况下强制循环连续？

提前致谢！