Sara de la Rosa de Sáa

According to our database, Sara de la Rosa de Sáa authored at least 14 papers between 2012 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2021

Location-Free Robust Scale Estimates for Fuzzy Data.

Sara de la Rosa de Sáa, María Asunción Lubiano, Beatriz Sinova, María Ángeles Gil, Peter Filzmoser

IEEE Trans. Fuzzy Syst., 2021

2018

Descriptive Comparison of the Rating Scales Through Different Scale Estimates: Simulation-Based Analysis.

Irene Arellano, Beatriz Sinova, Sara de la Rosa de Sáa, María Asunción Lubiano, María Angeles Gil

Proceedings of the Uncertainty Modelling in Data Science, 2018

2017

Hypothesis testing-based comparative analysis between rating scales for intrinsically imprecise data.

María Asunción Lubiano, Antonia Salas, Carlos Carleos, Sara de la Rosa de Sáa, María Angeles Gil

Int. J. Approx. Reason., 2017

Robust scale estimators for fuzzy data.

Sara de la Rosa de Sáa, María Asunción Lubiano, Beatriz Sinova, Peter Filzmoser

Adv. Data Anal. Classif., 2017

2016

Descriptive analysis of responses to items in questionnaires. Why not using a fuzzy rating scale?

María Asunción Lubiano, Sara de la Rosa de Sáa, Manuel Montenegro, Beatriz Sinova, María Angeles Gil

Inf. Sci., 2016

The mean square error of a random fuzzy vector based on the support function and the Steiner point.

Beatriz Sinova, Sara de la Rosa de Sáa, María Rosa Casals, María Angeles Gil, Antonia Salas

Fuzzy Sets Syst., 2016

Hypothesis testing for means in connection with fuzzy rating scale-based data: algorithms and applications.

María Asunción Lubiano, Manuel Montenegro, Beatriz Sinova, Sara de la Rosa de Sáa, María Angeles Gil

Eur. J. Oper. Res., 2016

An Empirical Analysis of the Coherence Between Fuzzy Rating Scale- and Likert Scale-Based Responses to Questionnaires.

María Asunción Lubiano, Antonia Salas, Sara de la Rosa de Sáa, Manuel Montenegro, María Ángeles Gil

Proceedings of the Soft Methods for Data Science, 2016

2015

Fuzzy Rating Scale-Based Questionnaires and Their Statistical Analysis.

Sara de la Rosa de Sáa, María Angeles Gil, Gil González-Rodríguez, María Teresa López, María Asunción Lubiano

IEEE Trans. Fuzzy Syst., 2015

An Overview on the Statistical Central Tendency for Fuzzy Data Sets.

Beatriz Sinova, Sara de la Rosa de Sáa, María Asunción Lubiano, María Angeles Gil

Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2015

2014

On the Robustness of Absolute Deviations with Fuzzy Data.

Sara de la Rosa de Sáa, Peter Filzmoser, María Ángeles Gil, María Asunción Lubiano

Proceedings of the Strengthening Links Between Data Analysis and Soft Computing, 2014

Empirical Sensitivity Analysis on the Influence of the Shape of Fuzzy Data on the Estimation of Some Statistical Measures.

María Asunción Lubiano, Sara de la Rosa de Sáa, Beatriz Sinova, María Ángeles Gil

Proceedings of the Strengthening Links Between Data Analysis and Soft Computing, 2014

2013

A generalized L¹-type metric between fuzzy numbers for an approach to central tendency of fuzzy data.

Beatriz Sinova, Sara de la Rosa de Sáa, María Angeles Gil

Inf. Sci., 2013

2012

Fuzzy Rating vs. Fuzzy Conversion Scales: An Empirical Comparison through the MSE.

Sara de la Rosa de Sáa, María Angeles Gil, María Teresa López García, María Asunción Lubiano

Proceedings of the Synergies of Soft Computing and Statistics for Intelligent Data Analysis, 2012