![]() ![]() However, it is returning the same values of peak correlation and lag repeated throughout output dataframe. About Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How YouTube works Press Copyright Contact us Creators Advertise. Then I used following function to find peak correlation: Find_Abs_Max_CCF = maxcor-maxcor*e & absres$abscor % group_by(files) %>% group_map(~Find_Abs_Max_CCF(datframe$f, dataframe$m, 0.05)) #obtaining observations of first file entry Technical Bid (as per NIT), any bid with a shorter bid validity. Past studies on country-level FDI have Table 1. ![]() This paper contributes to the literature by providing fresh evidence on the effect of perceived corruption on FDI using time series data. This type of country-level study is crucial to introducing efficient policies to attract FDI. I have so far could measure the peak cross-correlation of the files individually: file1 % filter(file = unique(dataframe$`Begin File`)) 1 The bid shall remain valid for a minimum period of 180 days from the date of opening of the. corruption on FDI in Egypt have not yet been investigated. More specifically I want the output to be a dataframe with three columns: recording file names, peak correlation score between female and male, and the lag value (at which peak correlation occurred). ![]() I want to find at which lags the female and male are most correlated for all different recordings. The 'files' column represent recording file names, 'Time' represents discretised time bins of 0.1 seconds, the 'Male' and 'Female' column represents whether the male and female are calling (1) or not (0) during that time bin. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |