corrgram - Plot a Correlogram
Calculates correlation of variables and displays the results graphically. Included panel functions can display points, shading, ellipses, and correlation values with confidence intervals. See Friendly (2002) <doi:10.1198/000313002533>.
Last updated 2 months ago
18 stars 5.42 score 0 dependencies 3 dependentsagridat - Agricultural Datasets
Datasets from books, papers, and websites related to agriculture. Example graphics and analyses are included. Data come from small-plot trials, multi-environment trials, uniformity trials, yield monitors, and more.
Last updated 2 months ago
data
112 stars 4.63 score 0 dependencies 3 dependentspals - Color Palettes, Colormaps, and Tools to Evaluate Them
A comprehensive collection of color palettes, colormaps, and tools to evaluate them.
Last updated 2 months ago
77 stars 4.50 score 4 dependencies 7 dependentsdesplot - Plotting Field Plans for Agricultural Experiments
A function for plotting maps of agricultural field experiments that are laid out in grids. See Ryder (1981) <doi:10.1017/S0014479700011601>.
Last updated 2 months ago
22 stars 2.78 score 33 dependencies 4 dependentslucid - Printing Floating Point Numbers in a Human-Friendly Format
Print vectors (and data frames) of floating point numbers using a non-scientific format optimized for human readers. Vectors of numbers are rounded using significant digits, aligned at the decimal point, and all zeros trailing the decimal point are dropped. See: Wright (2016). Lucid: An R Package for Pretty-Printing Floating Point Numbers. In JSM Proceedings, Statistical Computing Section. Alexandria, VA: American Statistical Association. 2270-2279.
Last updated 2 months ago
25 stars 2.35 score 2 dependenciesnipals - Principal Components Analysis using NIPALS or Weighted EMPCA, with Gram-Schmidt Orthogonalization
Principal Components Analysis of a matrix using Non-linear Iterative Partial Least Squares or weighted Expectation Maximization PCA with Gram-Schmidt orthogonalization of the scores and loadings. Optimized for speed. See Andrecut (2009) <doi:10.1089/cmb.2008.0221>.
Last updated 2 months ago
7 stars 2.14 score 0 dependencies 4 dependentsclustertend - Check the Clustering Tendency
Calculate some statistics aiming to help analyzing the clustering tendency of given data. In the first version, Hopkins statistic is implemented. See Hopkins and Skellam (1954) <doi:10.1093/oxfordjournals.aob.a083391>.
Last updated 1 years ago
1.85 score 0 dependenciesgge - Genotype Plus Genotype-by-Environment Biplots
Create biplots for GGE (genotype plus genotype-by-environment) and GGB (genotype plus genotype-by-block-of-environments) models. See Laffont et al. (2013) <doi:10.2135/cropsci2013.03.0178>.
Last updated 2 months ago
7 stars 1.68 score 12 dependencieslookup - Functions Similar to VLOOKUP in Excel
Simple functions to lookup items in key-value pairs. See Mehta (2021) <doi:10.1007/978-1-4842-6613-7_6>.
Last updated 2 months ago
3 stars 1.43 score 0 dependencies 1 dependentsmountainplot - Mountain Plots, Folded Empirical Cumulative Distribution Plots
Lattice functions for drawing folded empirical cumulative distribution plots, or mountain plots. A mountain plot is similar to an empirical CDF plot, except that the curve increases from 0 to 0.5, then decreases from 0.5 to 1 using an inverted scale at the right side. See Monti (1995) <doi:10.1080/00031305.1995.10476179>.
Last updated 2 months ago
1 stars 1.18 score 1 dependencieshopkins - Calculate Hopkins Statistic for Clustering
Calculate Hopkins statistic to assess the clusterability of data. See Wright (2023) <doi:10.32614/RJ-2022-055>.
Last updated 2 months ago
2 stars 1.12 score 3 dependenciespagenum - Put Page Numbers on Graphics
A simple way to add page numbers to base/ggplot/lattice graphics.
Last updated 2 months ago
0.86 score 0 dependenciesrseedcalc - Estimating the Proportion of Genetically Modified Seeds in Seedlots via Multinomial Group Testing
Estimate the percentage of seeds in a seedlot that contain stacks of genetically modified traits. Estimates are calculated using a multinomial group testing model with maximum likelihood estimation of the parameters.
Last updated 11 years ago
0.00 score 0 dependencies