Hi As Thierry points out INLA is certainly one way to go. Very powerful. For some inspiration see the tutorials and example on the INLA web site. Perhaps the geostatinla package for R (http://pbrown.ca/geostatsp/document-rev.pdf) can be of use for you. Also the section on geoadditive models in http://www.rni.helsinki.fi/~jmh/mrf08/R-INLA.pdf may give you some ideas.
The nlme package for R can fit the same kind of models, see e.g. http://www.ats.ucla.edu/stat/r/faq/spatial_regression.htm. Yours sincerely / Med venlig hilsen Frede Aakmann Tøgersen Specialist, M.Sc., Ph.D. Plant Performance & Modeling Technology & Service Solutions T +45 9730 5135 M +45 2547 6050 [email protected] http://www.vestas.com Company reg. name: Vestas Wind Systems A/S This e-mail is subject to our e-mail disclaimer statement. Please refer to www.vestas.com/legal/notice If you have received this e-mail in error please contact the sender. > -----Original Message----- > From: [email protected] [mailto:r-sig-geo-bounces@r- > project.org] On Behalf Of ONKELINX, Thierry > Sent: 25. september 2014 09:27 > To: Justice Moses K. Aheto; [email protected] > Subject: Re: [R-sig-Geo] Spatial and multilevel model with > kriging/interpolation in R > > Have a look at the INLA package (www.r-inla.org) > > Best regards, > > ir. Thierry Onkelinx > Instituut voor natuur- en bosonderzoek / Research Institute for Nature and > Forest > team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance > Kliniekstraat 25 > 1070 Anderlecht > Belgium > + 32 2 525 02 51 > + 32 54 43 61 85 > [email protected] > www.inbo.be > > To call in the statistician after the experiment is done may be no more than > asking him to perform a post-mortem examination: he may be able to say > what the experiment died of. > ~ Sir Ronald Aylmer Fisher > > The plural of anecdote is not data. > ~ Roger Brinner > > The combination of some data and an aching desire for an answer does not > ensure that a reasonable answer can be extracted from a given body of data. > ~ John Tukey > > -----Oorspronkelijk bericht----- > Van: [email protected] [mailto:r-sig-geo-bounces@r- > project.org] Namens Justice Moses K. Aheto > Verzonden: donderdag 25 september 2014 4:25 > Aan: [email protected] > Onderwerp: [R-sig-Geo] Spatial and multilevel model with > kriging/interpolation in R > > Dear All, > Please, I wish to analyse a spatial data in R through multilevel approach with > my main primary objective been to interpolate for unsampled locations in my > study region. Children in my data set are nested within households in the > study locations and my multilevel model (without spatial) showed significant > household random effects hence my choice to employ spatial analysis with > multilevel approach. > The need to include household random effects in my spatial model makes it a > bit difficult for me to implement in R unlike the standard geostatical > analysis. > I have 'SpatialPointsDataFrame' containing my geographical coordinates > (longitude and latitude) as well as my response and covariates. > The spatial mixed effects model I wish to fit and interpolate is: Yij(t) = > Xij(t)β > +hj+S(t)+Ɛij (1) > where > i=individual child, j=household, X(t)= spatial referenced non-random > covariates, S(t)= spatially correlated stationary Gaussian process. > Ɛij =nugget effect/measurement error, Yij(t) = response of child i in > household j at location t and is a continuous variable, hj =household level > random effects and β=regression coefficients (spatial trend parameter). > Specifically, S(t)~N(0,σ2H11(ɸ) ), where σ2 is the variance (partial sill), > H11(ɸ) is the correlation matrix based on valid correlation function h(u; ɸ), > where u is the distance between locations and ɸ is the correlation parameter > (range). > hj~N(0, σ2h), where σ2h is the household level variance Ɛij~N(0,τ2), where > τ2 is the nugget effect/measurement error. > > I am trying to achieve the above task through geostatistical analysis but > other > methods which can be implemented in R are also welcomed. > > > Please, could somebody help me with some papers in the literature, existing > packages in R which are related to my problem as well as providing me with R > codes to implement this assuming someone has already done this kind of > multilevel spatial regression and interpolation in R or other packages. > > Many thanks for your help in advance. > > > Kind regards > > ***************************************** > Justice Moses K. Aheto > PhD Candidate in Medicine (United Kingdom) MSc Medical Statistics (United > Kingdom) BSc Statistics (Ghana) HND Statistics (Ghana) > > Chief Executive Officer > Statistics and Analytics Consultancy Services Ltd. > > Skype: jascall12 > Mobile: > +447417589148. > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Geo mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > * * * * * * * * * * * * * D I S C L A I M E R * * * * * * * * * * * * * > Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer > en binden het INBO onder geen enkel beding, zolang dit bericht niet > bevestigd is door een geldig ondertekend document. > The views expressed in this message and any annex are purely those of the > writer and may not be regarded as stating an official position of INBO, as > long > as the message is not confirmed by a duly signed document. > _______________________________________________ > R-sig-Geo mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-geo _______________________________________________ R-sig-Geo mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-geo
