Dear R-users,
I have imported a shapefile with depth contours for a sea:
depths-read.shape(D://My Documents/BarentsSea.shp,dbf.data=T)
(This is in mercator projection)
**Is there a way to convert this shapefile into a format that it may be
plotted on a contour plot?**
I wish to add these
Dear All,
This is probably a very basic question but:
I have plotted a map of the Barents Sea and surrounding coastline using:
map('worldHires',ylim=c(50,85),xlim=c(5,65),fill=T,resolution=0)
map.axes()
map.scale(x=30,metric=T)
Next, I imported a shapefile with depth contours for the sea:
I am trying to fit a generalised least squares model using gls in the nlme
package.
The model seems to fit very well when I plot the fitted values against the
original values, and the model parameters have quite narrow confidence
intervals (all are significant at p5%).
The problem is that the
I am trying to fit a generalised least squares model using gls in the nlme
package.
The model seems to fit very well when I plot the fitted values against the
original
values, and the model parameters have quite narrow confidence intervals
(all are
significant at p5%).
The problem is that the
Dear List,
I have multiple time series, all of which (excepting 1) have missing
values. These run for ~30 years, with monthly sampling. I need to
determine stationarity, and have tried to use the Augmented Dickey-Fuller
test (adf.test), but this cannot handle missing values. The same problem
Dear List,
The purpose of this e-mail is to ask about R time series procedures - as a
biologist with only basic time series knowledge and about a year's
experience in R.
I have been using ARIMAX models with seasonal components on seasonal data.
However I am now moving on to annual data (with
I have just started using R for my PhD. I am importing my data from Excel
via notepad into Word. Unfortunately, my data has many missing values. I
have put '.' and this allowed me to import the data into R. However, I
now want to interpolate these missing values. Please can someone give me
