![]() ![]() I would like to turn these Inf values into NA values. ![]() Restricted permutations using the permute package In R, I have an operation which creates some Inf values when I transform a dataframe. Vegan (≥ 2.0-0), testthat (≥ 0.5), parallel, knitr, rmarkdown, bookdown, sessioninfo The 'permute' package is modelled after the permutation schemes of 'Canoco 3.1' (and later) by Cajo ter Braak. 'permute' also allows split-plot designs, in which the whole-plots or split-plots or both can be freely-exchangeable or one of the restricted designs. It seems that with poor models R is more restrictive and does not show standard errors.Permute: Functions for Generating Restricted Permutations of DataĪ set of restricted permutation designs for freely exchangeable, line transects (time series), and spatial grid designs plus permutation of blocks (groups of samples) is provided. If you have any suggestions on how I could provide a replicable example (maybe with some sample panel data, any suggestions?), I will gladly do so.Ī smaller model produces identical results in R and Stata. Viewed 8k times 10 Please consider the following: I recently discovered the awesome plyr and dplyr packages and use those for analysing patient data that is available to me in a data frame. Ask Question Asked 4 years, 8 months ago. Inthe case of a numeric or integer vector, a vector of length 1 can beused and it will be expanded to a vector of length object(i.e., 1:object) before. ![]() ![]() objectcan be one of a data frame, matrix, an objectfor which a scores method exists, or a numeric or integer vector. Function numPermsreturns the number of permutations for thepassed objectand the selected permutationscheme. I have 2 class labels, but when I permute, I have an index value for each sample in my data and the permutation hence should not be done for each row in the data but permute Class label (CL) for each index in the data. 0211975 -3.32 0.001 -.1119261 -.0288333Ġ3 |. a list of control values describing properties of thepermutation design, as returned by a call tohow. Also, this is a little similar to one of the questions you had solved using your package. Group variable: id Number of groups = 15,945 The issue is: why do I get standard errors in Stata but "Inf" in R? Conditional fixed-effects Poisson regression Number of obs = 110,233 The results in Stata (see below) yield standard errors and where the standard errors are significant the coefficients are very much the same as in R, so I assume in both cases the same model was calculated. performance data and returns reports to help customer manage system. Xtpoisson x1 x3 x3_lag x3_lag2 season x4 x1#x3_lag x1#x3_lag2 x1#x4, fe Disk Busy KBPS TPS KB-R ART MRT KB-W AWT MWT AQW AQD. number of ways of ordering, permuting, or arranging r out of n objects. Other density-based methods follow a slightly different approach. An infinite list is called a sequence There are things called 1) List: a1. My code in R is (formula shortened for illustration): library(pglm) The algorithm then proceeds with the next unclustered object. In R language, NULL (capital letters) is a reserved word and can also be the product of importing data with unknown data type. Unfortunately I cannot upload and share the data due to legal restrictions. In general, R supports: NULL NA NaN Inf / -Inf NULL is an object and is returned when an expression or function results in an undefined value. I'm running a fixed-effects Poisson regression and get different results in Stata and R. ![]()
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