search for: daylength

...and 2007. This was not the case, the solstice should vary by one day between these years. Code is provided below and any help is appreciated. Patrick ps. apologies to you southern ducks your summer and winter solstices are reversed of my code nomenclature. I'm working with a northern dataset. Daylength <- function(J,L){ #Amount of daylight #Ecological Modeling, volume 80 (1995) pp. 87-95, "A Model Comparison for Daylength as a Function of Latitude and Day of the Year." #D = Daylight length #L = Latitude in Degrees #J = Day of the year (Julian) P <- asin(.39795*cos(.2163108 + 2*ata...

Hello all, I have a (hopefully) simple question. If I have a data table (named "x") such as this: daylengthleavesflowering.datefruits LD1.90055581.64353250.76668986 LD-0.9399410-1.2592968-0.60141837 LD1.0222946-0.9697459 -0.60141837 SD-0.2668132-0.9697459-0.47363322 SD -1.5892393-0.70540660.66469785 SD -0.5222961-0.7054066-0.10701187 How do create a new data table that contains, e.g., only the long-day...

...on algorithmus that calculates day wise values (values are depenend from the output of the day before). First I create a data.frame with NAs. Finally each row contains the daily values. output <- as.data.frame(matrix(nrow = 365, ncol = 50)) for (day in (1:365)) { ... r <- list(Date=d,daylength=daylength,TempSum=tempsum, ...) output[day,] <- r } Is there an better (faster) way to do such things in R? Greetings Christof

...re, barometric pressure), and tides (dummy variables for high, falling, low, and rising).  So predictors are binary, categorical, and continuous variables.  I ran glm.nb to fit my full model containing all first order terms.  The model I ran was: glm.nb.full<glm.nb(mantas~site+year+cosday+sinday+daylength+lunarpercent+sstmean+sststd+ sshmean+sshstd+cosdir+sindir+spd+temp+alt+tideht+high+falling+low+plankton)   However, when I use stepAIC on the model I get the message:   > stepAIC(glm.nb.full) Start:  AIC=19240.46 mantas ~ site + year + cosday + sinday + daylength + lunarpercent +     sstmean +...

...ot; but that didn't seem to help.  I didn't know of the na.omit function.  It made it much easier to get rid of all the missing values in the file, and now the regression model is running. I hadn't put interactions in the model yet since it wasn't even running.  Cosday, sinday, and daylength are strongly collinear.  The full model with interactions keeps all three in, plus all interactions between them. Thanks for your help! Tim [[alternative HTML version deleted]]

...] Simple question about extracting a subset of data To: R Help <r-help at r-project.org> Message-ID: <192025.49678.qm at web110113.mail.gq1.yahoo.com> Content-Type: text/plain Hello all, I have a (hopefully) simple question. If I have a data table (named "x") such as this: daylengthleavesflowering.datefruits LD1.90055581.64353250.76668986 LD-0.9399410-1.2592968-0.60141837 LD1.0222946-0.9697459 -0.60141837 SD-0.2668132-0.9697459-0.47363322 SD -1.5892393-0.70540660.66469785 SD -0.5222961-0.7054066-0.10701187 How do create a new data table that contains, e.g., only the long-day...