Problems with dcc function of the treeclim package

[Granato-Souza]

Hello, I'm having problems trying to truncate the timespan of the correlation analysis when I'm using dcc function on treeclim package.

rpb.dcc<dcc(rpb.crn,precip,selection=.range("precip",-6:12),method="correlation",dynamic="moving",win_size=25,win_offset=5,start_last=TRUE,timespan=NULL,var_names="precip",ci=0.05,boot="stationary",sb=TRUE)

Both of my data start in 1902-2016 but I would like to truncate both in 1939-2016. When I type ...,timespan=(1939:2016)... R doesn't recognize the time interval. Can anyone help me with that?

[technocrat]

Thanks for including some code. Next time it would help to have some data and the code in the form of FAQ: What's a reproducible example (`reprex`) and how do I do one?

Here's a solution, assuming your data set is in the form of norw015

> library(dplyr)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

> library(tibble)
> library(treeclim)
Loading required package: Rcpp
> data(norw015)
> head(norw015)
        xxxstd samp.depth
1600 0.6317956          1
1601 0.3966429          1
1602 0.3718675          1
1603 0.4002325          1
1604 0.3752488          1
1605 0.5385194          1
> norw <- rownames_to_column(norw015, var = "year")
> head(norw)
  year    xxxstd samp.depth
1 1600 0.6317956          1
2 1601 0.3966429          1
3 1602 0.3718675          1
4 1603 0.4002325          1
5 1604 0.3752488          1
6 1605 0.5385194          1
> norw_years <- norw %>% filter(year > 1935)
> head(norw_years)
  year    xxxstd samp.depth
1 1936 0.9608494         34
2 1937 1.0050585         34
3 1938 0.9518574         34
4 1939 0.9265154         34
5 1940 0.8521800         34
6 1941 1.2747496         34
> norw_36 <- column_to_rownames(norw_years, var = 'year')
> head(norw_36)
        xxxstd samp.depth
1936 0.9608494         34
1937 1.0050585         34
1938 0.9518574         34
1939 0.9265154         34
1940 0.8521800         34
1941 1.2747496         34

[Granato-Souza]

Thank you very much, yes, my data is in the form of norw015. I'm going to apply it.

All the best

Daniela