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  • How to best impute missing values of county-level time series . . .
    I'm looking for an imputation method that takes into account temporal, spatial correlation as well as the association with some sociodemographic county-level variables such as income, education, and so forth
  • Impacts of spatial imputation on location-allocation problem . . .
    This paper explores how spatial imputation exploiting spatial autocorrelation can contribute to estimating missing values in a weights surface for location modeling and subsequently improve solutions for spatial optimization, specifically p-median problems using a spatially imputed weights surface This paper examines two spatial imputation
  • Extending multilevel spatial models to include spatially . . .
    Methodologically, extending multilevel models to allow intercepts and slopes to vary spatially is straightforward The purpose of this paper, therefore, is to show how multilevel spatial models can be extended to include spatially varying covariate effects
  • Spatial Analysis Modeling - Census. gov
    Incorporation of spatially-correlated random effects in small area models Model-based methods for prediction at low geographic levels Mean-squared error, uncertainty, and interval estimation
  • Multiple Imputation: Methods and Applications - Duke University
    Incorporate all sources of uncertainty in imputations, including uncertainty in parameter estimates Want models that accurately describe the distribution of missing values Important to keep in mind that imputation model used only for cases with missing data 30% missing values
  • Machine Learning of Spatial Data — A Critical Review
    We can either incorporate spatial data and its features directly into the machine learning models and algorithms or create spatial features and feed the spatial data into non-spatial
  • Multiple Imputation with Mplus
    Conducting multiple imputation (MI) can sometimes be quite intricate In this note we provide some general guidance on this process using Mplus The statistical modeling behind the multiple imputation method in Mplus Version 6 is somewhat complex


















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