Questions tagged [regression]
In statistical modeling, regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables.
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sDNA learn - AIC
Is there a way to show the model AIC as output to sDNA learn, in addition to mean GEH and r2? Perhaps by adding a line in sdnaregutilities?
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Trying to run logistic (binary) regression in QGIS using 2 polygon layers, but unsure which tool to use
I am trying to use a polygons layer A with continuous values as an independent variable and a polygons layer B with binary 1 and 0 values as the dependent variable in a logistic regression to see ...
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Interpreting r.regression.multi
I cannot find a source that explains how to interpret the output of r.regression.multi. Can someone explain what the different lines mean; specifically how do I see if the results are significant?
X=...
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R.regression.multi land-use data not enough valid cells
What I want: run r.regression.multi between land-use change and bumblebee occurrence.
What I did:
X coefficients: cov_all.0 of North, East, South and West SSP1 -4 layers in total. (I projected the ...
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Multiple linear regression returning gaps (nulls)
I am using multiple linear regression by ee.Reducer.linearRegression reducer fuction. I have 3 independents ('x1', 'x2', 'x3' ) and 1 dependent ('y').
When I using any combination of 2 independents ...
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Tree Cover Density raster layer: is it considered a categorical raster?
I am using the Tree Cover Density (TCD) raster layer from EEA. The raster has integer values from 0-255, where each integer represents the percentage of tree cover density.
I want to use a machine ...
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Pixel-wise multivariable regression to estimate solar irradiance from Worldclim data
I want to do a pixel-wise multivariable regression to predict missing "srad13" and "srad14" data where "srad" is the dependent variable using the independent variable ...
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Pixel-wise regression between the independent variables tmax, tmin, prec and the depending variable srad after they are clipped in R [duplicate]
I have WorldClim version 2.1 climate data for 1970-2000. This version was released in January 2020.
There are monthly climate data for minimum, mean, and maximum temperature, precipitation, solar ...
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Spatial statistics -- geographically weighted regression
I have some count data (electric vehicle chargers). I'm trying to model its relationship with % of cars that are electric within an area. They show linear correlation.
Normally I would use Poisson ...
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How to use terra::predict with mixed model?
I developed a model from a dataset where zmean and zpcum5 are continuous values, and V6 is categorical (evergreen, mixed, deciduous).
Lm3c.ranslope <- lmer(plotVol_sqrt ~ zmean + zpcum5 + I(zmean * ...
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Calculate a correction factor between two sets of data
I'm a data science student and have a problem with harvesting data.There are two sets of geographic data (stored as points) that stores the yield of a soybeans harvest in the same field, they are from ...
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Print chart error: "User memory limit exceed"
I tried to plot the SAR backscattering vs the Crop Water Stress Index using the following code:
var CWSI= ndvi.add(ndwi).rename('CWSI')
print('CWSI',CWSI)
Map.addLayer(CWSI.clip(Hoshiarpur),{},"...
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Rolling (moving) window linear regression - extract residuals
I want to perform linear regression with a rolling (moving) window with size 5 using raster data.
I tried a code using the raster package and the function localFun, and when I am trying to export the ...
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Use non-linear regression output to predict values across raster including categorical attributes
We are aiming to correct general snow depth values from publicly available layers at a coarse resolution (~1km) using our vegetation and other parameters collected in the field at point locations ...
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Moran's I in panel data using contiguity matrix
I have some data in a panel format and want to run some spatial panel regression. In a cross-sectional framework, I would run a simple regression and test the spatial autocorrelation from the ...
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Reusing regression or machine learning model in subsequent years
I have collected high-resolution UAV imagery and leaf area index (LAI) plot data. I plan on creating a model which uses my ground-based LAI to establish a relationship or train my UAV imagery. I will ...
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R predict() a future table value in a time series
I have tree canopy information measured for 5 trees over 4 dates in the following CSV:
treeID,X,Y,Z,area,date
1278,888260,936944,58.8,40.7,2021-09-22
1278,888262,936940,53.6,66.3,2021-10-15
1278,...
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Forest-based classification and regression error 110180 using ArcGIS Pro
I tried to train a model to predict a binary output, while I used 12 bands from Sentinel-2 satellite images as the explanatory training raster, but there's an error showed that there was not enough ...
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Earth Engine: minimumDistance classifier in regression mode
The minimumDistance classifier in GEE uses the nearest neighbor procedure to predict a class (in classification mode) or a real value (in regression mode). The parameter "Knearest" set by ...
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I need to print RMSE but don't know why error is coming
I need to print root mean squared error (RMSE) but don't know why error is coming. Can any one share code how I can calculate RMSE?
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Linear regression analysis in R [closed]
I would like to conduct a simple linear regression analysis in R with two grids. So I have two Raster images of the same region and I need to do a regression analysis, but I struggle with doing that. ...
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Perform a Thiel-Sen regression on a raster stack in R
I have a raster stack of 20 layers. Each layer represent accumulated NDVI values for the growing season for each year spanning my period of study.
I want to perform a trend analysis using Thiel-Sen ...
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Second order regression in QGIS
I am trying to calibrate nighttime light raster images. The data is available from 1992 to 2012 captured by different satellite and variation in the sensor too. Now in order to use the data for time ...
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Calculating R-Squared Using the 'Residuals' Band from Google Earth Engine's linearRegression() Reducer
I am trying to calculate an R-Squared for a harmonic linear regression I did with two dependent variables across an image collection, using the linearRegression reducer on Google Earth Engine. The ...
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Setting up Generalized Linear Regression in ArcGIS Pro
I am analyzing a series of old canals and I am trying to make the case that these are tied to certain physical characteristics (soil, slope, etc) in the watershed. To check wether or not my hypothesis ...
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Regression in QGIS
I have point rainfall and temperature values for a district and a few sample yield points for the same. How do I interpolate the yield points for the whole district wrt the rainfall and temperature? ...
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Regression using spatio-temporal data
I'm trying to implement a regression using R, but the various models I have tried so far do not predict well at all.
The dataset I'm working with consists of roughly 10,000 observations which ...
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Creating probability of occurrence map in ArcMap Pro
I am trying to figure out how to create a map representing probability of some phenomena occurrence. I have a binary raster (1- phenomena exists; 0 - doesn't exist) and several raster that explain ...
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Surf3D, example from ggRandomForests: Random Forests for Regression
I have a model and I want to use the surf3D function in R, and produce a plot similar to the following (the image is the example from "ggRandomForests: Random Forests for Regression").
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Spatial regression: general nesting spatial model using splm package in R
I have a shapefile of panel data (multiple years of observations for each polygon). I am estimating fixed effects spatial regression models with this data. I used one year of this data to generate a ...
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Regression Analysis
How can I perform a regression analysis between image reflection and field data in Google Earth Engine platform?
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What Explained Variance is good to proceed with Predictive Soil Mapping?
I have 1851 soil samples data on pH covering a study area of 7482sq.km in northern Ghana and I am using 52 environmental long-term average variables (Relief, Climate, MODIS Reflectances and derived ...
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Training Random Forest using more than 5,000 samples
I'm estimating forest biomass using Random Forest regression at a large scale. I want to train the Random Forest model using as many samples as possible (~100,000 samples), but it seems the Google ...
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Interpreting results of GWR - what do the values mean?
I used R to run a Geographically Weighted Regression (GWR) model.
The resulting model comes with a bunch of values that are given in a table. These are:
sum.w
X.Intercept, X.Intercept_se (standard ...
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QGIS Regression Tools using only feature data
I'm trying to find in QGIS an analogous tool to ArcGIS's "Ordinary Least Squares". The tool takes in a shapefile, where the dependent variable and independent variables are all fields in ...
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Linear Regression Error in GEE
I am trying to create a correlation chart between NDVI and LST. Everything working fine except the error message saying Error generating chart: FeatureCollection.randomPoints: Polygon too large to be ...
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When to use spatial regression for the proximity analysis
I am not sure about whether I should use spatial regression for the proximity analysis I am trying to do.
I’ll just describe the scenario and goal:
People claim that convenience stores lower nearby ...
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Testing for spatial autocorrelation in residuals of OLS regression
I'm currently working on a dataset that is most likely to have spatial autocorrelation issues.
In particular, I have observations at the region level and I'm trying to run a regression to check ...
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Focal regression 3x3 group of cells
I have two raster with same resolution and dimension: water-occurrence index and rainfall (mm). I want to create a new raster of SLOPE (a) and INTERCEPT (b) by performing linear regression between ...
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Linear regresion at each raster pixel's value to predict future value (in R language)
I want to predict future value with existing time series raster. For simplicity, I want use linear regression at each raster pixel's value to predict future value
I have successfull run this code. I ...
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Google Earth Engine: Evaluate classifier of output type regression
Background
According to the Google Earth Engine documentation for supervised classification, the accuracy assessment of classifiers such as ee.Classifier.smileRandomForest can be done using a ...
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Memory allocation problem when running Random forest regression in python
I have image with 4 bands . I want to see if I can predict the first band using the 3 other bands.
My problem is that I cannot fit the model because I get the following error message:
MemoryError: ...
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Multiple linear regression between grids: reviewing the assumptions
I am performing a regression analysis with three raster stacks in R.
This worked so far.
Now I want to check the conditions of the model and I am not sure how exactly that should work in this case. ...
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How to apply convolutional neural network over a time series of Landsat images
I am implementing a fully convolutional neural network (specifically U-Net) over a time series of Landsat 8 images to predict land cover change. I am following the demo notebook for the predictions. ...
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Ordinary Least Squares Point Aggregation
I want to run an ordinary least squares regression in ArcGIS Pro on my dataset which is composed of about 400 fire occurrences (point data) and demographic variables (100x100m polygons of income, ...
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What is missing in my spatial lag equation model?
I worked it in GeoDa but I think something is missing.
What is the right equation for a spatial lag model?
In my understanding to predict a variable Y is as follows:
Y = w_t_homi100 + CONSTANT + ...
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modifiedmk Mann-Kendall Test Over NC /Raster stack
I am working with NetCDF file for analysis of trend. I am using the following codes for analysis of trend..
library(modifiedmk)
library(raster)
I <- brick("I.nc")
d <- stack(I)
...
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Display R2 in GEE chart
I have created scatter plot in GEE but for some reason it doesn't display the R2 and the way the linear regression displayd is also not good:
as you can see. the R2 isn't displayed at all and the ...
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Export fitted values from time series regression in Google Earth Engine
I have used harmonic regression to model NDVI values in GEE. Now I would like to export fitted values for every half-month timestep. Unfortunately, much of the exported cells rasters have 'nodata', ...
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How to select one band in image using rasterio
I have two different images and I want to select one specifi band from each one of them and calculate regression between them. Each one of those bands is a result of calculation I did (in the first ...
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