Error in if (pvals[minp] <= pent) { : argument is of length zero - r

Question

I am very new to R and I am trying to write general functions instead of very specific ones for a certain file. I am trying to do Land Use Regression(Using olsrr package). My code looks like this:
library("olsrr")
library("car") #check VIF
library("heplots")
dataset <- read.csv("data.csv")
View(dataset)
dim(dataset) #991 observations with 79 variables
summary(dataset)
summary(dataset[,c("PM25","NOx","PM10","O3")]) # The outcome variables are not nuerice format
###################
# Data Management #
###################
# Convert air pollution data (PM2.5) into numeric format #
dataset$PM25 <- as.numeric(as.character(dataset$PM25))
dataset$NOx <- as.numeric(as.character(dataset$NOx))
dataset$PM10 <- as.numeric(as.character(dataset$PM10))
dataset$O3 <- as.numeric(as.character(dataset$O3))
summary(dataset[,c("PM25","NOx","PM10","O3")]) # issue solved!!
#############
# Remove NA #
#############
dataset <- na.omit(dataset)
dim(dataset) #957 observations remained
###############################
# Stepwise Regression Model #
# (olsrr Package) #
###############################
#### Set the varaibles will be used for LUR ####
Y <- colnames(dataset)[8] # Outcome variable [PM2.5]
X <- colnames(dataset)[9:ncol(dataset)] # predictors
allX <- paste(X, collapse = "+") # put all predictors together
as.formula(paste(Y, "~", allX)) # Check formula for linear model
temp <- lm(as.formula(paste(Y, "~", allX)), singular.ok=TRUE, data=dataset)
summary(temp)
#### Stepwise regression ####
stepResult <- ols_step_both_p(model=temp, pent=0.1, prem=0.3, details=FALSE)
but When I run the 'ols_step_both_p' funtion. R give me a message:
Error in if (pvals[minp] <= pent) { : argument is of length zero
so what should I do?

Answer 1

This looks like a bug in the olsrr package. Please share a reproducible example using reprex.
PS. I am the author of olsrr. You can directly contact me using the mail id provided on the CRAN page.