1.2 R代码 library(fitdistrplus) descdist(data, discrete = FALSE, boot = NULL, method = "unbiased 14.5 8.3 28.9 3.1 7.3 10.2 8.9 0.1 15.5 5.7 0.7 8.3 0.9 40.7 2.9 分析: library(fitdistrplus 参考文献 https://cran.r-project.org/web/packages/fitdistrplus/fitdistrplus.pdf
tidyr, htmlwidgets, shiny, igraph, reticulate, spatstat.core, SeuratObject, plotly, pbapply, lmtest, fitdistrplus
plot(fit) + labs(y = "Estimated parameters") + theme_minimal(base_family = "myfont") 结果提供了 lambda 与 fitdistrplus
", "gplots", "dtw", "SDMTools", "plotly", "Hmisc", "httr", "tidyr", "ggridges", "metap", "lmtest", "fitdistrplus
同时通过fitdistrplus,extraDistr来进行去除后评价 数据准备 既然是在线分析,第一步还是要上传我们准备好的数据。在这个工具当中,主要是上传两个文件: 1.
5.0.0 Depends: R (≥ 4.0.0), methods, SeuratObject (≥ 5.0.0) Imports: cluster, cowplot, fastDummies, fitdistrplus
查看依赖关系: p_depends(Seurat) $Depends [1] "methods" $Imports [1] "cluster" "cowplot" "fitdistrplus
gplots’, ‘Rcpp’, ‘dtw’, ‘SDMTools’, ‘plotly’, ‘Hmisc’, ‘httr’, ‘tidyr’, ‘ggridges’, ‘metap’, ‘lmtest’, ‘fitdistrplus reshape2","gplots","Rcpp","dtw","SDMTools","plotly","Hmisc","httr","tidyr","ggridges","metap","lmtest","fitdistrplus