A modified nested-error regression model for small area estimation

Herrador, M.; Esteban, Maria J.; Hobza, Tomáš; Morales, Domingo

doi:10.1080/02331888.2011.599068

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…Where the variables of interests cannot be described by standard linear models, nested-error regression model having both fixed and random effects are usually applied to include Monte Carlo simulation methodology in order to enhance representative precision. Nested-error modeling is better at regional spatial scales and performs poorly at large scale spatial coverage [9].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Crop Yields under a Changing Climate

Juma¹,

Beru²

2021

Agrometeorology

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The impact of increasing climate variability on crop yield is now evident. Predicting the potential effects of climate change on crops prompts the use of statistical models to measure how the crop responds to climate variables. This chapter examines the usage of regression analysis in predicting crop yield under a changing climate. Data quality control is explained and application of descriptive statistics, correlation analysis and contingency tables discussed. Methodological aspects of crop yield modeling and prediction using climate variables are described. Estimation of yield via a multilinear regression approach is outlined and an overview of statistical model verification introduced. The study recommends the usage of regression models in estimating crop yield in consideration of many other externalities that can contribute to yield change.

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Section: Introductionmentioning

confidence: 99%

Prediction of Crop Yields under a Changing Climate

Juma¹,

Beru²

2021

Agrometeorology

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Model-Based Estimation of Small Area Dissimilarity Indexes: An Application to Sex Occupational Segregation in Spain

Bugallo,

Morales,

Esteban

et al. 2024

Soc Indic Res

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This paper introduces a new statistical methodology for estimating Duncan dissimilarity indexes of occupational segregation by sex in administrative areas and time periods. Given that direct estimators of the proportion of men (or women) in the group of employed people for each occupational sector are not accurate enough in the considered estimation domains, we fit to them a three-fold Fay–Herriot model with random effects at three hierarchical levels. Based on the fitted area-level model, empirical best predictors of the cited proportions and Duncan segregation indexes are derived. A parametric bootstrap algorithm is implemented to estimate the mean squared error. Some simulation studies are included to show how the proposed predictors have a good balance between bias and mean squared error. Data from the Spanish Labour Force Survey are used to illustrate the performance of the new statistical methodology and to give some light about the current state of sex occupational segregation by province in Spain. Research claims that there is a sex gap that persists despite advances in the inclusion of women in the labour market in recent years and that is related to the unequal sharing of family responsabilities and the stigmas still present in modern societies.

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Comparison of EBLUP and EBLUP Modification in Estimating Small Areas (Study : Percentages of Poverty in Bogor District)

Merdeka

Sadik

Indahwati

2018

IJSRSET

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A small area of the sample occurs when the sample size is very small. A large error will get if the parameters estimation is done with small the sample. One method to overcome it using a small area estimation (SAE) method. A small area estimator is a statistical technique to estimate the parameters of a sub-population with a small sample size. Estimates in the small area estimator method is based on the model and are indirect estimates. In this study the indirect method used is the EBLUP method and the modification of EBLUP estimator. The results of the alleged percentage of poverty in the Bogor district show that the EBLUP modification method is better compared to the expected method directly. This is based on the average of the RRMSE obtained.

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A modified nested-error regression model for small area estimation

Cited by 3 publications

References 13 publications

Prediction of Crop Yields under a Changing Climate

Prediction of Crop Yields under a Changing Climate

Model-Based Estimation of Small Area Dissimilarity Indexes: An Application to Sex Occupational Segregation in Spain

Comparison of EBLUP and EBLUP Modification in Estimating Small Areas (Study : Percentages of Poverty in Bogor District)

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