The implementation of the Huang-Ogata method is experimental Hard core radius) or choose a different interaction. Zero at a data point, this means that the model is Locations, indicating that the model forbids the presence of a Points), the conditional intensity may be zero at some spatial “N data points are illegal (zero conditional intensity)” The error message gives a further explanation,Ĭhoose a simpler model, or check the data.
It is not possible to estimate all the model parametersįrom this dataset. Undefined, it would be prudent to check that the pixel imagesĪre correct, and are correctly registered in their spatial relation to However if more than a few percent of covariate values are To be one-pixel-width narrower than the observation window. Is small, this warning can be ignored - typically it happensīecause of rounding effects which cause the pixel image Spatial domain of the pixel image does not completely cover the Values of the covariate at some of the spatial locations in the The covariate data (typically a pixel image) did not provide “Covariate values were NA or undefined at X% Very large numbers, or if the covariates are approximatelyĬollinear. Singularity can also occur if the covariate values are Kilometres by X <- rescale(X, 1000), then re-fit the Rescale the data, for example, to convert from metres to expressed in metres) so that the fitted coefficients were Singularity usually occurs because the spatialĬoordinates in the original data were very large numbers This error is usually reported when the model is printed,īecause the print method calculates standard errors for theįitted parameters.
#PPP FRAME VERTICAL FORMAT SOFTWARE#
The Fisher information matrix of the fitted model has aĭeterminant close to zero, so that the matrix cannot be inverted,Īnd the software cannot calculate standard errors or confidence intervals. Some common error messages and warning messagesĪre listed below, with explanations. The hard core radius will then be estimated from the data. Hard core interaction as interaction=Hardcore() To specify the interaction without giving The hard-core radius in the model HardcoreĪnd the matrix of hard-core radii in MultiHard can beĮstimated easily from data. Some irregular parameters can be estimated directly from data: Useful techniques include maximum profile pseudolikelihood, whichĪnd Newton-Raphson maximisation, implemented in the Practical techniques, but no general statistical theory available. To determine the irregular parameters, there are several Regular parameter \(\gamma\) has been estimated. The result of this command will be a fitted model in which the Note that the value of the irregular parameter r must be given. For example, to fit a Strauss process model to the cellsĭataset, you could type ppm(cells, ~1, Strauss(r=0.07)).
It requires the values of any irregular parameters of the interaction The ppm command is only designed to estimate regular Of interpoint inhibition, and an irregular parameter \(r\) Has a regular parameter \(\gamma\) controlling the strength Of the interaction, while irregular parameters determine the Typically, regular parameters determine the ‘strength’ \(\theta = \theta(\psi)\) is some transformation of If the log likelihood is a linear function of \(\theta\) where These parameters are of two types: regular parameters: Range of ‘interaction’ or dependence between points.
Ppm has parameters that determine the strength and Apart from the Poisson model, every point process model fitted by
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