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Remove overlaps and zonal statistics will perform as expected. Extract from tool help: If the zone feature input has overlapping polygons, the zonal analysis will not be performed for each individual polygon. Since the feature input is converted to a raster, each location can only have one value. An alternative method is to process the zonal ...


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If this is a linear referenced network then create an event table with two measures (i.e., the midpoint measure you calculate in step 1 and a second measure at X distance offset from the midpoint measure). Then if the values you want to sum are also events then you can merge the event tables using Overlay Route Events. This will only merge events on the ...


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QGIS Time Manager is appropriate for this : https://plugins.qgis.org/plugins/timemanager/ You must have a single shapefile with every features. Each features must have a time Start and End attribut. When you play the slider, features will animate according this. If you want to use this as a web map, I suggest you Lealfet Timeline (quite the same ...


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You have to treat the @data slot (the data frame) a bit differently to reduce the number of attributes / columns: Set the working directory and load the right library require(rgdal) setwd("~/workspace/TEMP/") Make a fake SPDF to work with, as OP describes pts <- data.frame(x=1:5, y=1:5, A = 1:5, B = 1, C = 2, D = 3) coordinates(pts) <- ~x+y ...


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I think you need to subset your dataset using bracket notation. As an example: point_pattern <- point_pattern[point_pattern$A == 1,]


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I dont know the similar function for QGIS, but in ArcMap you need to be in edit mode, then there is a tool that merges the polygons then another tool that dissolves them into one polygon. In QGIS you should be looking for a similar function.


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I think the goodness of fit measure you are looking for is a chi-squared. For which (I believe) your 'minimum weighted sum of squares' IS your goodness of fit statistic. Assuming this or this is what you are doing. Reading about the packages on CRAN can sometimes be helpful. This thread will also be relevant. Or you could google: "calculate R2 weighted sum ...



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