Message-ID: <176F26A1DA36AE4FA85D1D6502858F820568D1@BY2PRD0810MB356.namprd08.prod.outlook.com>
Date: 2012-11-05T15:29:27Z
From: Corey Sparks
Subject: Question about space-time analysis routines
In-Reply-To: <ADE85578-3A5F-4B70-A6EF-9FEDFB069E8B@msu.edu>
Thank you gentlemen, this gives me some things to work with.
Best to all
Corey
On Nov 5, 2012, at 6:48 AM, Andrew Finley wrote:
> Hi,
> The new package spTimer might be another option.
> -Andy
>
> On Nov 5, 2012, at 5:56, Virgilio G?mez-Rubio <virgilio.gomez at uclm.es> wrote:
>
>> Hi,
>>
>>> I am curious if the list can point me to some other libraries in R, besides
>>> INLA, that are capable of using the spacetime data directly in a regression
>>
>> INLA is a good software to fit spatiotemporal models as it is very
>> flexible.
>>
>>> framework, or perhaps in a spatio-temporal disease clustering framework. I
>>> know about the DCluster library and use it some, but would be very grateful
>>> for any other ideas.
>>
>> You may want to check DClusterm :
>>
>> https://r-forge.r-project.org/projects/dclusterm/
>>
>> It is underdevelopment but it implements space-time clustering and
>> spatial clustering based on GLMs.
>>
>> Best,
>>
>> Virgilio
>>
>> _______________________________________________
>> R-sig-Geo mailing list
>> R-sig-Geo at r-project.org
>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>
>
Corey Sparks, PhD
Assistant professor
Department of Demography
The University of Texas at San Antonio
501 West Cesar E Chavez Blvd
San Antonio TX 78207
Corey.sparks 'at' utsa.edu
210 458 3166
Latitude: 29.423614 / Longitude: -98.504282