?s 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
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