Hello R users,
I'm working with a time-series of several years and to analyze it, I’m using
GAM smoothers from the package mgcv. I’m constructing models where
zooplankton biomass (bm) is the dependent variable and the continuous
explanatory variables are:
-time in Julian days (t), to creat a long-
Here is my approximation:
# Creation of the temporal variables
DF$year <- as.numeric(format(DF$date, format = "%Y"))
DF$month <- as.numeric(format(DF$date, format = "%m"))
# For years with data from 2006 to 2008
DF_type1 <- DF [ - which (year == 2006 & month ==1 | year == 2006 & month ==
2 |
You're totally right Jeff. My mistake! to use with, we write it like this:
DF$season <- factor ( with ( *DF*, ifelse (( month == 12 | nonth == 1 |
month == 2 ), "Win",
ifelse ((month == 3 | nonth == 4 | month == 5 )
, "Spr",
ifelse
For me it owrks when i write it like:
as.Date(paste(mydata$Delivery.Date), "%m/%d/%Y")
Hope it works,
Regards,
Ricardo
--
View this message in context:
http://r.789695.n4.nabble.com/as-date-do-not-know-how-to-convert-mydata-1-to-class-Date-tp4638691p4638696.html
Sent from the R help mailin
- About the visualization, my question is more about interpretation. In the
case of :
model_name <- gam ( bm ~ t + te (t_year, temp_W, temp_sept, k = 5, bs = c(
“cc”,”cr”,”cr”)), data = data)
* a)* vis.gam (model_name , view= c(“t_year”, “temp_W”))
*b)* vis.gam (model_name , view= c(“t_year
- About the first question, I was not sure about what was the proper model (
a) or b) ) because I saw this at the end of the help for te ---> ?te :
n <- 500
v <- runif(n);w<-runif(n);u<-runif(n)
f <- test2(u,v,w)
y <- f + rnorm(n)*0.2
# tensor product of 2D thin plate regression spline and 1D c
6 matches
Mail list logo
