The seas package for the R programming environment is capable of conveying descriptive statistics and graphics for seasonal variables, as found in climatology, hydrology and ecology. Seasonal variables can be continuous (e.g., temperature) or discontinuous (e.g., precipitation). An annum can be partitioned into many arbitrary divisions, or seasonal components, such as by month or into other fixed intervals. Boxplots are used to describe the seasonal distributions of continuous variables. Discontinuous variables need to be summed over time to smooth the irregularities before the variable can be evaluated and visualized. Statistics, such as precipitation normals, may be derived from the summed variables, using the mean or median methods. Other tools and utilities provided in the package can calculate precipitation interarrivals, cumulative precipitation departures, find changes between two normals and import data from archive formats.
[1]
David R. Kincaid,et al.
Numerical mathematics and computing
,
1980
.
[2]
Irma J. Terpenning,et al.
STL : A Seasonal-Trend Decomposition Procedure Based on Loess
,
1990
.
[3]
John M. Chambers,et al.
Graphical Methods for Data Analysis
,
1983
.
[4]
N. Guttman,et al.
The Use of L-Moments in the Determination of Regional Precipitation Climates
,
1993
.
[5]
Beat Kleiner,et al.
Graphical Methods for Data Analysis
,
1983
.
[6]
J. R. Wallis,et al.
Regional Frequency Analysis: An Approach Based on L-Moments
,
1997
.
[7]
H. Storch,et al.
Statistical Analysis in Climate Research
,
2000
.
[8]
N. Guttman,et al.
Statistical Descriptors of Climate
,
1989
.
[9]
Alex J. Cannon,et al.
Recent variations in seasonality of temperature and precipitation in Canada, 1976–95
,
2002
.