However, the method suggested by Seafoid and Keith of pre-creating all combinations with massively redundant numbers of rows might not scale to genome-scale numbers of SNPs if you're doing all combinations (say, N=500,000 or more). In data analysis it is often nice to look at all pairwise combinations of continuous variables in scatterplots. Compute all pairwise combinations of indices. I have also written some functions for calculating combinations and permutations in R, and shown examples of using the gtools package to list out all possible permutations; I wrote the functions to replicate the formulae in R. A note that Yamanaka-sensei, didn’t actually go about checking all the combinations. Vignettes. In this recipe we replace multiplication with string concatenation (paste), and the result is all combinations of strings. self. Check if all pairwise combinations of elements of input.seq are contained in twopt. Package index. pairwise_combination_indices: Compute all pairwise combinations of indices In MESS: Miscellaneous Esoteric Statistical Scripts Description Usage Arguments Details Value Author(s) Examples mmollina/MAPpoly Construction of Genetic Linkage Maps in Autopolyploids. Fast computation of indices of all pairwise element of a vector of length n. Usage pairwise_combination_indices(n, self = FALSE) Arguments n. A number giving the number of elements to create all pairwise indices from. Up until recently, I have used the function splom in the package lattice, but ggplot2 has superior aesthetics, I think anyway. R: Generating All Pairwise Combinations of Strings Yao Yao on February 7, 2015. rdrr.io Find an R package R language docs Run R in your browser R Notebooks. I am looking for a smart way to generate all pairwise combinations of two vectors of length n, where only one value is not zero. Search the mmollina/MAPpoly package. A logical that determines whether a column should also be multiplied by itself. Here a few ways to accomplish the task: All pairwise combinations. For now I am doing something quite desperate with loops through each I agree that apply is in general a great approach. aq_standardize: Rescale AQ score given specific mean and variance import_sre: Import SRE dataset loo_table: table of LOO comparisons merge_data_and_posterior: Merge posterior predictions with data pairwise: All pairwise combinations pipe: Pipe operator pooled_sd: Hedges G posterior_aq_action_contrasts: Univariate form with renamed variables
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