statistics - Running many multiple OLS regressions at once in R -


i want run time series regressions (fama-french 3 factor new factor). have following tables.

table01      date     port_01  port_02 --------- port_18     01/1965     0.85    0.97               1.86     02/1965     8.96    7.2                0.98     03/1965     8.98    7.9                8.86   table 02      date        market   smb    hml     wxo     01/1965      0.85    0.97    0.86    0.87     02/1965      8.96    7.2     0.98    0.79     03/1965      8.98     7.9    8.86    0.86

i have run 18 regressions , store intercepts in vector. this

      port_1=inter(1)+beta1(market)+beta2(smb)+beta3(hml)+beta3(wxo)+e       port_2=inter(2)+beta1(market)+beta2(smb)+beta3(hml)+beta3(wxo)+e       port_18=inter(18)+beta1(market)+beta2(smb)+beta3(hml)+beta3(wxo)+e

i want these 18 intercepts stored in vector. can individually. if there way coding me lot of time.

consider vapply(), variant of lapply() allows specification of output here being atomic numeric vector (length of 1). however, first, need merge tables date field , create list of port formulas (assuming that's needed underlying data). below runs linear regression, lm, adjust actual model might require adjusting intercept extraction:

data <- merge(table_01, table_02, by="date")  ports <- colnames(table_01)[2:ncol(table_01)]     formulas <- paste(ports, "~ market + smb + hml + wxo")  intercepts <- vapply(formulas, function(i) {                            output <- lm(i, data)                           coef(output)["(intercept)"]                      }, numeric(1))

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