Description Usage Arguments Value See Also
Compute various statistics for functional data using numerical integration when needed. A total of 7 statistics are available in the package and the user can even define its own statistic for use within the statistical test functions.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | stat_hotelling(x, y = NULL, mu = NULL, paired = FALSE, step_size = 0)
stat_L1(x, y = NULL, mu = NULL, paired = FALSE, step_size = 0)
stat_L1_std(x, y = NULL, mu = NULL, paired = FALSE, step_size = 0)
stat_L2(x, y = NULL, mu = NULL, paired = FALSE, step_size = 0)
stat_L2_std(x, y = NULL, mu = NULL, paired = FALSE, step_size = 0)
stat_Linf(x, y = NULL, mu = NULL, paired = FALSE, step_size = 0)
stat_Linf_std(x, y = NULL, mu = NULL, paired = FALSE, step_size = 0)
stat_all(x, y = NULL, mu = NULL, paired = FALSE, step_size = 0)
|
x |
Dataframe or matrix containing the data collected from 1st population. |
y |
Dataframe or matrix containing the data collected from 2nd
population (default: |
mu |
True mean value (or difference between mean values) under the null
hypothesis (default = |
paired |
Is the input data paired? (default: |
step_size |
The step size used to perform integral approximation via the
method of rectangles (default: |
All stat_*
functions return a named numeric vector of size 1
storing the value of the corresponding statistic except stat_all
that outputs a vector of size 7 containing the values of all 7 statistics
currently available in the fdahotelling package.
A detailed description of the individual statistics for functional data provided by the fdahotelling package can be found in the vignette Available statistics for functional data.
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