Thanks again,
Tom
-Original Message-
From: Gavin Simpson [mailto:ucfa...@gmail.com]
Sent: Thursday, September 05, 2013 6:35 PM
To: Worthington, Thomas A
Cc: r-help@r-project.org
Subject: Re: [R] Assessing temporal correlation in GAM with irregular time steps
On 3 September 2013 16:
> Best wishes
> Tom
>
> -Original Message-
> From: Gavin Simpson [mailto:ucfa...@gmail.com]
> Sent: Tuesday, September 03, 2013 3:17 PM
> To: Worthington, Thomas A
> Cc: r-help@r-project.org
> Subject: Re: [R] Assessing temporal correlation in GAM with irregular time
> st
l.com]
Sent: Tuesday, September 03, 2013 3:17 PM
To: Worthington, Thomas A
Cc: r-help@r-project.org
Subject: Re: [R] Assessing temporal correlation in GAM with irregular time steps
It is possible, but you can't use the discrete time or classical stochastic
trend models (or evaluate using the ACF
It is possible, but you can't use the discrete time or classical
stochastic trend models (or evaluate using the ACF). Also, why do you
care to do this with regard to DoY? The assumption of the model
relates to the residuals, so you should check those for residual
autocorrelation.
As you are using
I have constructed a GAM using the package mgcv to test whether the lengths of
an emerging insect (Length) varies with day of the year (DOY) and between two
sites (SiteCode). The data are collected at irregular time steps ranging from 2
days to 20 days between samples. The GAM takes the form
M3
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