What is he best known for?
The fields of study he is best known for:
- Statistics
- Regression analysis
- Machine learning
Antonio Páez focuses on Travel behavior, Econometrics, Statistics, Human factors and ergonomics and Discrete choice.
His study with Travel behavior involves better knowledge in Transport engineering.
Antonio Páez has researched Econometrics in several fields, including Goodness of fit, Cross-validation and Regression.
His Smoothing and Spatial analysis study, which is part of a larger body of work in Statistics, is frequently linked to Local regression, bridging the gap between disciplines.
Antonio Páez combines subjects such as Injury prevention and Suicide prevention with his study of Human factors and ergonomics.
His work carried out in the field of Discrete choice brings together such families of science as Scholarship, Trip generation and Economic model.
His most cited work include:
- Measuring accessibility: positive and normative implementations of various accessibility indicators (301 citations)
- Spatial statistics for urban analysis: A review of techniques with examples (238 citations)
- Sustainable Urban transportation: Performance indicators and some analytical approaches (185 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Travel behavior, Transport engineering, Econometrics, Public transport and Economic growth.
His study focuses on the intersection of Travel behavior and fields such as Trip generation with connections in the field of Ordered probit.
His Transport engineering research integrates issues from Economies of agglomeration, Regional science and Geographic information system.
His studies examine the connections between Econometrics and genetics, as well as such issues in Spatial analysis, with regards to Regression analysis.
While the research belongs to areas of Public transport, he spends his time largely on the problem of Sample, intersecting his research to questions surrounding Mode.
His Economic growth study combines topics from a wide range of disciplines, such as Population ageing, Demographic economics and Transport policy.
He most often published in these fields:
- Travel behavior (17.26%)
- Transport engineering (16.67%)
- Econometrics (16.07%)
What were the highlights of his more recent work (between 2018-2021)?
- Context (7.14%)
- Sample (5.36%)
- Catchment area (1.79%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Context, Sample, Catchment area, Global South and Mode.
His Sample study incorporates themes from Poverty, Cognitive dissonance, Public transport and Happiness.
His Public transport research is multidisciplinary, incorporating perspectives in Promotion, Transport corridor, Road pricing and Geodemographic segmentation.
His Catchment area research incorporates a variety of disciplines, including Inequality, Health care, Environmental planning, Float and Variable.
Along with Global South, other disciplines of study including Duration, Motorized vehicle, Attractiveness and Transport engineering are integrated into his research.
His Mode research incorporates themes from Developing country, Contrast and Demographic economics.
Between 2018 and 2021, his most popular works were:
- A Spatio-Temporal Analysis of the Environmental Correlates of COVID-19 Incidence in Spain. (25 citations)
- Measuring relative non-motorized accessibility to retail activities (12 citations)
- Using Google Community Mobility Reports to investigate the incidence of COVID-19 in the United States (8 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Machine learning
- Regression analysis
The scientist’s investigation covers issues in Incidence, Measure, Public economics, Equity and Social exclusion.
His Incidence research spans across into fields like Set, Statistics, Interpretability, Baseline and Population density.
As part of his studies on Measure, Antonio Páez often connects relevant subjects like Data science.
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