CAST Laboratory

Research and development in probability sampling, survey methodology and computational tools for Agricultural Surveys.

People

Every Lab is only as good as its team. CAST is fortunate enough to work with talented & creative researchers.

Researchers

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Hemílio Coelho

Professor of Sampling Statistics

Sampling Statistics, Computational Statistics, Statistical Methods

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Andréa Diniz

Researcher at IBGE

Record Linkage, Populational Studies, Data Analysis

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Cristiano Ferraz

Professor of Sampling Statistics

Sampling Statistics, Statistical Methods, Agricultural Statistics

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André Leite

Professor of Operations Research

Operations Research & Analytics, Computational Statistics, Machine Learning

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Raydonal Ospina

Professor of Remote Sensing

Remote Sensing, Machine Learning, Data Modelling

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Marcel Vieira

Professor of Sampling Statistics

Sampling Statistics, Longitudinal Data Analysis, Survey Data Analysis

Grad Students

Alumni

Projects

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Estimação resistente em modelos de regessão beta inflacionados

Projeto Individual Institucional - Cadastro Propesq - UFPE / 2018

Npar y Datos

Dessarrollo de métodos basados en rachas y rangos para varios tipos de problemas de hipótesis con diferentes modelos muestrales, en problemas de regresión y de modelos lineales.

Apps for Agricultural Statistics

Tools for supporting sampling design and data collection are under development, prioritizing new technologies.

External Project

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Internal Project

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Master Frames for Agricultural Statistics

Master sampling frames for generating agricultural and rural statistics.

Recent Publications

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Research on the metaphorical mapping of valenced concepts onto space indicates that positive, neutral, and negative concepts are mapped …

Following the 2015 publication of the Handbook on Master Sampling Frames for Agricultural Statistics: Frame Development, Sample Design …

Statistical and probabilistic reasoning enlightens our judgments about uncertainty and the chance or beliefs on the occurrence of …

In this paper, we present an approach for minimizing the computational complexity of the trained convolutional neural networks …

In dynamical systems, some of the most important questions are related to phase transitions and convergence time. We consider a …

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