| Title: | Calculates the Statistical Significance of a Trend in a Set of Measurements |
| Version: | 0.0.0.3 |
| Description: | Detection of a statistically significant trend in the data provided by the user. This is based on the a signed test based on the binomial distribution. The package returns a trend test value, T, and also a p-value. A T value close to 1 indicates a rising trend, whereas a T value close to -1 indicates a decreasing trend. A T value close to 0 indicates no trend. There is also a command to visualize the trend. A test data set called gtsa_data is also available, which has global mean temperatures for January, April, July, and October for the years 1851 to 2022. Reference: Walpole, Myers, Myers, Ye. (2007, ISBN: 0-13-187711-9). |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.2.3 |
| Depends: | R (≥ 2.10) |
| LazyData: | true |
| Imports: | pheatmap |
| NeedsCompilation: | no |
| Packaged: | 2022-12-16 16:58:57 UTC; CSERHMX |
| Author: | Matthew Cserhati 
[aut, cre] |
| Maintainer: | Matthew Cserhati <csmatyi@protonmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2022-12-19 09:30:06 UTC |
Calculates The Statistical Significance Of A Teend In A Set Of Measurements
Description
The package calculates whether there is a statistically significant trend in the date provided by the user. This is based on the a signed test based on the binomial distribution. The package returns a trend test value, T, and also a p-value. A T value close to 1 indicates a rising trend, whereas a T value close to -1 indicates a decreasing trend. A T value close to 0 indicates no trend. There is also a command to create a heatmap visualizing the trend.
Version 0.0.1. Author: Dr. Matthew Cserhati Email: csmatyi@protonmail.com December 14, 2022
Arguments
data |
a data frame with the measurement values |
Value
The p-value and trend value of the data
References
Walpole, Myers, Myers, Ye. (2007) Probability & Statistics for Engineers and Scientists. Upper Saddle River, NJ, Pearson Prentice Hall.
Examples
meas <- c(1.1,4.5,7.8,5.9,10.2)
binomialtrend(meas)
binomialtrend(c(1,2,3,4,2,4,5,6,8,5,4,7,10,11))
CRUTEM World Mean Temperature Data Set from 1851 to 2022
Description
CRUTEM World Mean Temperature Data Set from 1851 to 2022
Usage
gsta_data
Format
gsta_data
A data set with 172 rows and 4 columns, for Jan, Apr, Jul and Oct from 1851-2022
- Jan
world mean temperature for January
- Apr
world mean temperature for April
- Jul
world mean temperature for July
- Oct
world mean temperature for October
Source
https://crudata.uea.ac.uk/cru/data/temperature/CRUTEM.5.0.1.0.stat4post.txt.gz
Calculates The Statistical Significance Of A Teend In A Set Of Measurements
Description
The package calculates whether there is a statistically significant trend in the date provided by the user. This is based on the a signed test based on the binomial distribution. The package returns a trend test value, T, and also a p-value. A T value close to 1 indicates a rising trend, whereas a T value close to -1 indicates a decreasing trend. A T value close to 0 indicates no trend. There is also a command to create a heatmap visualizing the trend.
Version 0.0.1. Author: Dr. Matthew Cserhati Email: csmatyi@protonmail.com December 14, 2022
Arguments
data |
a data frame with the measurement values |
Value
nil
References
Walpole, Myers, Myers, Ye. (2007) Probability & Statistics for Engineers and Scientists. Upper Saddle River, NJ, Pearson Prentice Hall.
Examples
meas <- c(1.1,4.5,7.8,5.9,10.2)
trendmap(meas)
trendmap(c(1,2,3,4,2,4,5,6,8,5,4,7,10,11))