Covariates in lgcp

[who]

Hello, I was wondering if INLA is the only method to fit a Log Gaussian Cox Process without covariates.

Best regards,

James

[Daniel Simpson]

Hi James,

There are a number of packages that fit LGCPs.  (We only have one of them, so this information isn't complete.) 

- The lgcp package fits LGCPs using a modern MCMC routine.

- The spatstat package fits LGCPs using non-Bayesian methods (the spatstat::lgcp.estK uses minimum contrast estimation)

- The geostatsp package provides a nice (and easy to use!) wrapper to the INLA package.

I hope this helps.

Dan

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[who]

Hi Daniel,

first of all thank you very much for the answer. I am interested in MCMC inference and so I am trying to implement the lgcp package. However I have some troubles in fitting the model without covariates; it seems that I must specify a design matrix, but I do not need it in my study. Do you know if it is possible to do it?

Thank you for your time,

Best regards,

James

[Daniel Simpson]

Sorry. You'll have to contact Ben Taylor who wrote the package. 

Dan

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[who]

I definitely will.

Thanks again for your help.

Il giorno venerdì 8 aprile 2016 15:27:49 UTC+2, Daniel Simpson ha scritto:

Sorry. You'll have to contact Ben Taylor who wrote the package. 

Dan

On Friday, 8 April 2016, who <reginaele...@gmail.com> wrote:

Hi Daniel,

first of all thank you very much for the answer. I am interested in MCMC inference and so I am trying to implement the lgcp package. However I have some troubles in fitting the model without covariates; it seems that I must specify a design matrix, but I do not need it in my study. Do you know if it is possible to do it?

Thank you for your time,

Best regards,

James

Il giorno venerdì 8 aprile 2016 02:02:40 UTC+2, who ha scritto:

Hello, I was wondering if INLA is the only method to fit a Log Gaussian Cox Process without covariates.

Best regards,

James

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