Nothing
## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE)
knitr::opts_chunk$set(warning = FALSE, message = FALSE)
## ----eval=FALSE---------------------------------------------------------------
# library("RHRV")
#
# basePath <- "book_data" # adjust as needed
# NSR_DB <- file.path(basePath, "normal")
# CHF_DB <- file.path(basePath, "chf")
# HEALTHY_DB <- file.path(basePath, "healthy")
## ----eval=FALSE---------------------------------------------------------------
# spreadsheetPath <- basePath
## ----eval=FALSE, results=FALSE------------------------------------------------
# easyAnalysis <- RHRVEasy(folders = c(NSR_DB, CHF_DB), nJobs = -1)
## ----eval=FALSE---------------------------------------------------------------
# print(easyAnalysis)
## ----eval=FALSE---------------------------------------------------------------
# # HRVIndices
# head(easyAnalysis$HRVIndices)
## ----eval=FALSE---------------------------------------------------------------
# # Statistical analysis
# head(easyAnalysis$stats)
## ----results=FALSE, eval=FALSE------------------------------------------------
# easyAnalysisWavelet <- RHRVEasy(
# folders = c(NSR_DB, CHF_DB),
# typeAnalysis = 'wavelet',
# n_jobs = -1
# )
## ----eval=FALSE---------------------------------------------------------------
# easyAnalysisFDR <- RHRVEasyStats(easyAnalysis, correctionMethod = 'fdr')
# pValues <- merge(
# easyAnalysis$stats,
# easyAnalysisFDR$stats,
# by = setdiff(names(easyAnalysis$stats), "adj.p.value"),
# suffixes = c(".bonf", ".fdr")
# )
# #Let us compare the p-values obtained with different correction methods
# print(
# head(
# pValues[, c("HRVIndex", "p.value", "adj.p.value.bonf", "adj.p.value.fdr")]
# )
# )
## ----eval=FALSE---------------------------------------------------------------
# easyAnalysis <- RHRVEasy(folders = c(NSR_DB, CHF_DB),
# saveHRVIndicesInPath = spreadsheetPath)
## ----eval=FALSE---------------------------------------------------------------
# SaveHRVIndices(easyAnalysis, saveHRVIndicesInPath = spreadsheetPath)
## ----eval=FALSE---------------------------------------------------------------
# #Comparison of the three databases
# easyAnalysis3 <- RHRVEasy(
# folders = c(NSR_DB, CHF_DB, HEALTHY_DB),
# nJobs = -1
# )
# print(easyAnalysis3)
## ----eval=FALSE---------------------------------------------------------------
# print(head(easyAnalysis3$stats))
## ----eval=FALSE---------------------------------------------------------------
# # Let's print the post-hoc comparisons for "SDNN"
# print(head(easyAnalysis3$stats$pairwise[[1]]))
## ----results=FALSE, eval=FALSE------------------------------------------------
# easyAnalysisOverwritten <- RHRVEasy(folders = c(NSR_DB, CHF_DB),
# freqhr = 2,
# ULFmin = 0, ULFmax = 0.02,
# VLFmin = 0.02, VLFmax = 0.07,
# LFmin = 0.07, LFmax = 0.20,
# HFmin = 0.20, HFmax = 0.5)
## ----eval=FALSE---------------------------------------------------------------
# fullAnalysis <- RHRVEasy(
# folders = c(NSR_DB, CHF_DB, HEALTHY_DB),
# nJobs = -1,
# nonLinear = TRUE,
# doRQA = TRUE,
# saveHRVIndicesInPath = spreadsheetPath
# )
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