Às 17:57 de 30/11/2023, Rui Barradas escreveu:
Às 17:38 de 30/11/2023, Robert Baer escreveu:
I am having trouble using back ticks with the R extractor function
'predict' and an lm() model. I'm trying too construct some nice
vectors that can be used for plotting the two types of regression
intervals. I think it works with normal column heading names but it
fails when I have "special" back-tick names. Can anyone help with how
I would reference these? Short of renaming my columns, is there a way
to accomplish this?
Repex
*# dataframe with dashes in column headings
cob =
structure(list(`cob-wt` = c(212, 241, 215, 225, 250, 241, 237,
282, 206, 246, 194, 241, 196, 193, 224,
257, 200, 190, 208, 224
), `plant-density` = c(137, 107, 132, 135, 115, 103, 102, 65,
149, 85, 173, 124, 157, 184, 112, 80, 165,
160, 157, 119)),
class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -20L))
# regression model works
mod2 = lm(`cob-wt` ~ `plant-density`, data = cob)
# x sequence for plotting CI's
# Set up x points
x = seq(min(cob$`plant-density`), max(cob$`plant-density`), length =
1000)
# Use predict to get CIs for a plot
# Add CI for regression line (y-hat uses 'c')
# usual trick is to assign x to actual x-var name in middle dataframe
arguement
CI.c = predict(mod2, data.frame( `plant-density` = x), interval = 'c')
# fail
# Add CI for prediction value (y-tilde uses 'p')
# usual trick is to assign x to actual x-var name in middle dataframe
arguement
CI.p = predict(mod2, data.frame(`plant-density` = x), interval =
'p') # fail
*
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Hello,
When creating the new data df, the default check.names = TRUE changes
the column name, it is repaired and the hyphen is replaced by a legal dot.
# check.names defaults to TRUE
newd <- data.frame(`plant-density` = x)
# `plant-density` is not a column name
head(newd)
# check.names set to FALSE
newd <- data.frame(`plant-density` = x, check.names = FALSE)
# `plant-density` is becomes a column name
head(newd)
# Use predict to get CIs for a plot
# Add CI for regression line (y-hat uses 'c')
# usual trick is to assign x to actual x-var name in middle dataframe
arguement
CI.c = predict(mod2, newdata = newd, interval = 'confidence') # fail
# Add CI for prediction value (y-tilde uses 'p')
# usual trick is to assign x to actual x-var name in middle dataframe
arguement
CI.p = predict(mod2, newdata = newd, interval = 'prediction') # fail
Hope this helps,
Rui Barradas
Hello,
Sorry for the comments '# fail' in the last two instructions, I should
have changed them.
CI.c <- predict(mod2, newdata = newd, interval = 'confidence') # works
CI.p <- predict(mod2, newdata = newd, interval = 'prediction') # works
Hoep this helps,
Rui Barradas
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