#Set working directory to where "dynamicSLD.R" is located setwd("/Users/macw/Desktop/dynamic/") #See what files are in the current working directory list.files() #Load the functions source("dynamicSLD.R") #Confirm the environment now holds the dynamicSLD functions ls() ################################################################# #See the general trend of an individual #Expects a text file consisting of a single column headed with subject ID smooth("jorge.txt") #Optional parameter to indicate you want to plot on top of existing graph (instead of overwriting it) smooth("alberto.txt", TRUE) #See the general trend of an individual #Expects a vector smoothLocal(jorge) #See the "sliding window" of min-max differences between two individuals #Expects a tab-delimited text file consisting of two columns headed with subject IDs #Default window size is 5 minMax("jorge.txt") #Optional parameter to set window size: minMax("jorge.txt", 2) #Run Monte Carlo resampling to determine if one individual is more variable than another. #Returns a p-value (probability an individual is more variaible than another by chance) #Expects a tab-delimited text file consisting of two columns headed with subject IDs #Default number of resamplings is 5000 isMoreVariable("sampleData.txt") #Optional parameter to set number of resamplings: isMoreVariable("sampleData.txt", 10000) #Run Monte Carlo resampling to determine if an individual contains significant peaks. #Returns a p-value (how probable "peaks" were just by chance) #Expects a tab-delimited text file consisting of two columns headed with subject IDs #Default number of resamplings is 5000 hasSignificantPeaks("alberto.txt") #Optional parameter to set number of resamplings: hasSignificantPeaks("alberto.txt", 10000)