## S3 method for class 'numeric':
mean_sd(x, na.rm = TRUE, ...) ## S3 method for class 'matrix':
mean_sd(x, na.rm = TRUE, ...)
## S3 method for class 'hyperSpec':
mean_sd(x, na.rm = TRUE, ...,
short = "mean_sd", user = NULL, date = NULL)
## S3 method for class 'numeric':
mean_pm_sd(x, na.rm = TRUE, ...)
## S3 method for class 'matrix':
mean_pm_sd(x, na.rm = TRUE, ...)
## S3 method for class 'hyperSpec':
mean_pm_sd(x, na.rm = TRUE, ...,
short = "mean_sd", user = NULL, date = NULL)
## S3 method for class 'hyperSpec':
mean(x, na.rm = TRUE, ...,
short = "mean", user = NULL, date = NULL)
## S3 method for class 'hyperSpec':
quantile(x,
probs = seq(0, 1, 0.25), na.rm = TRUE, names = "num",
..., short = "quantile", user = NULL, date = NULL)
logentry
.quantile
"pretty"
results in percentages (like
quantile
's names = TRUE
),
"num"
results in the row names being
as.character (probs)
(good for ggplot2 gemean_sd
returns a vector with two values (mean and
standard deviation) of x
. mean_sd (matrix)
returns a matrix with the mean
spectrum in the first row and the standard deviation in
the 2nd.
mean_sd
returns a hyperSpec object with the mean
spectrum in the first row and the standard deviation in
the 2nd.
mean_pm_sd
returns a vector with 3 values: mean -
1 sd, mean, mean + 1 sd
mean_pm_sd (matrix)
returns a matrix containing
mean - sd, mean, and mean + sd rows.
For hyperSpec objects, mean_pm_sd
returns a
hyperSpec object containing mean - sd, mean, and mean +
sd spectra.
For hyperSpec object, mean
returns a hyperSpec
object containing the mean spectrum.
For hyperSpec object, quantile
returns a hyperSpec
object containing the respective quantile spectra.
mean
, sd
mean_sd (flu [,, 405 ~ 410])
mean_sd (flu$spc)
mean_sd (flu)
mean_pm_sd (flu$c)
mean_pm_sd (flu$spc)
mean_pm_sd (flu)
plot (mean (chondro))
plot (quantile (chondro))
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