Pennington statistics on a data frame or time series
Compute a table giving various descriptive statistics, including Pennington's estimators of the mean, the variance and the variance of the mean, about the series in a data frame or in a single/multiple time series
stat.pen(x, basic=FALSE, desc=FALSE)
x |
a data frame or a time series |
basic |
do we have to return also basic statistics (by default, it is FALSE)? These are: the number of values (nbr.val), the number of null values (nbr.null), the number of missing values (nbr.na), the minimal value (min), the maximal value (max), the range (range, that is, max-min) and the sum of all non-missing values (sum) |
desc |
do we have to return also various descriptive statistics (by default, it is FALSE)? These are: the median (median), the mean (mean), the standard error on the mean (SE.mean), the confidence interval of the mean (CI.mean) at the |
a data frame with the various statistics in rows and with each column correponding to a variable in the data frame, or to a separate time series
If you prefer to get separate statistics for various time intervals in your time series, use stat.slide(). Various other descriptive statistics, including test of the normal distribution are also available in stat.desc()
Frédéric Ibanez (ibanez@obs-vlfr.fr), Philippe Grosjean (phgrosjean@sciviews.org)
Aitchison, J., 1955. On the distribution of a positive random variable having a discrete probability mass at the origin. J. Amer. Stat. Ass., 50:901-908.
Pennington, M., 1983. Efficient estimations of abundance for fish and plankton surveys. Biometrics, 39:281-286.
data(marbio) stat.pen(marbio[,c(4, 14:16)], basic=TRUE, desc=TRUE)
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