Advanced Mathematical Approaches in Psycholinguistic Data Analysis: A Methodological Insight DOI Creative Commons
Cecília Castro, Víctor Leiva, Maria do Carmo Lourenço-Gomes

и другие.

Fractal and Fractional, Год журнала: 2023, Номер 7(9), С. 670 - 670

Опубликована: Сен. 5, 2023

In the evolving landscape of psycholinguistic research, this study addresses inherent complexities data through advanced analytical methodologies, including permutation tests, bootstrap confidence intervals, and fractile or quantile regression. The methodology philosophy our approach deeply resonate with fractal fractional concepts. Responding to skewed distributions data, which are observed in metrics such as reading times, time-to-response, time-to-submit, analysis highlights nuanced interplay between time-to-response variables like lists, conditions, plausibility. A particular focus is placed on implausible sentence response showcasing precision chosen methods. underscores profound influence individual variability, advocating for meticulous rigor handling intricate complex datasets. Drawing inspiration from mathematics, findings emphasize broader potential sophisticated mathematical tools contemporary setting a benchmark future investigations psycholinguistics related disciplines.

Язык: Английский

The log-cosine-power unit distribution: A new unit distribution for proportion data analysis DOI Creative Commons
Suleman Nasiru, Christophe Chesneau, Selasi Kwaku Ocloo

и другие.

Decision Analytics Journal, Год журнала: 2024, Номер 10, С. 100397 - 100397

Опубликована: Янв. 11, 2024

Continuous formulations of new distributions defined on the unit interval have gained attention because their relevance in modeling proportion data. We innovate this research direction by combining logarithmic, cosine, and power functions to create a log-cosine-power cumulative distribution function that defines distribution. The corresponding probability density has originality having tangent as primary term. Furthermore, graphical analysis shows can produce truly attractive model: is capable in-depth data exhibiting inverted-J, J, decreasing-constant-increasing shapes. This demonstrated using two datasets, results reveal it potential provide better parametric fit proportional than other existing with support interval.

Язык: Английский

Процитировано

10

A Statistical Framework for a New two-parameter Unit Bilal Distribution with Application to Model Asymmetric Data DOI Creative Commons
Tabassum Naz Sindhu, Anum Shafiq, Muhammad Bilal Riaz

и другие.

Heliyon, Год журнала: 2024, Номер unknown, С. e38340 - e38340

Опубликована: Сен. 1, 2024

Язык: Английский

Процитировано

8

The Continuous Bernoulli Distribution: Mathematical Characterization, Fractile Regression, Computational Simulations, and Applications DOI Creative Commons
Mustafa Ç. Korkmaz, Víctor Leiva, Carlos Martin‐Barreiro

и другие.

Fractal and Fractional, Год журнала: 2023, Номер 7(5), С. 386 - 386

Опубликована: Май 6, 2023

The continuous Bernoulli distribution is defined on the unit interval and has a unique property related to fractiles. A fractile position probability density function where corresponding surface fixed proportion. This article presents derivation of properties formulates or quantile regression model for response using exponentiated distribution. Monte Carlo simulation studies evaluate performance point estimators both model. Real-world datasets from science education are analyzed illustrate modeling abilities

Язык: Английский

Процитировано

12

Quasi-Cauchy Regression Modeling for Fractiles Based on Data Supported in the Unit Interval DOI Creative Commons
José Sérgio Casé de Oliveira, Raydonal Ospina, Víctor Leiva

и другие.

Fractal and Fractional, Год журнала: 2023, Номер 7(9), С. 667 - 667

Опубликована: Сен. 4, 2023

A fractile is a location on probability density function with the associated surface being proportion of such function. The present study introduces novel methodological approach to modeling data within continuous unit interval using or quantile regression. This has unique advantage as it allows for direct interpretation response variable in relation explanatory variables. new provides robustness against outliers and permits heteroscedasticity be modeled, making tool analyzing datasets diverse characteristics. Importantly, our does not require assumptions about distribution variable, offering increased flexibility applicability across variety scenarios. Furthermore, addresses mitigates criticisms limitations inherent existing methodologies, thereby giving an improved framework interval. We validate effectiveness introduced two empirical applications, which highlight its practical utility superior performance real-world settings.

Язык: Английский

Процитировано

6

A new quantile regression model with application to human development index DOI
Gauss M. Cordeiro, Gabriela M. Rodrigues, Fábio Prataviera

и другие.

Computational Statistics, Год журнала: 2023, Номер 39(6), С. 2925 - 2948

Опубликована: Сен. 22, 2023

Язык: Английский

Процитировано

5

Enhancing Software Cost Estimation using COCOMO Cost Driver Features with Battle Royale Optimization and Quantum Ensemble Meta-Regression Technique DOI
Preety Shoran, Anurag Sinha,

Hassan Raza Mahmood

и другие.

2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT), Год журнала: 2023, Номер unknown, С. 1 - 6

Опубликована: Июль 6, 2023

This research suggests a unique method for improving software cost estimates by combining Battle Royale Optimisation (BRO) and Quantum Ensemble Meta-Regression Technique (QEMRT) with COCOMO driver characteristics. The strengths of these three strategies are combined in the suggested strategy to increase accuracy estimation. model is popular cost-estimating methodology that considers several factors. BRO metaheuristic algorithm mimics process fittest people being selected naturally was inspired video game. benefits quantum computing ensemble learning machine approach known as QEMRT. Using correlation-based feature selection technique, we first identified most important drivers our study. To get best-fit model, then used optimize weights drivers. further estimation's accuracy, QEMRT utilized meta-regress optimized model. tested on two datasets estimating available public, outcomes were compared other cutting-edge approaches. experimental findings demonstrated beat approaches terms robustness, stability. In conclusion, offers viable estimation, which might help development organizations project planning resource allocation.

Язык: Английский

Процитировано

4

Inference Based on the Stochastic Expectation Maximization Algorithm in a Kumaraswamy Model with an Application to COVID-19 Cases in Chile DOI Creative Commons
Jorge Figueroa-Zúñiga,

Juan G. Toledo,

Bernardo Lagos

и другие.

Mathematics, Год журнала: 2023, Номер 11(13), С. 2894 - 2894

Опубликована: Июнь 28, 2023

Extensive research has been conducted on models that utilize the Kumaraswamy distribution to describe continuous variables with bounded support. In this study, we examine trapezoidal model. Our objective is propose a parameter estimation method for model using stochastic expectation maximization algorithm, which effectively tackles challenges commonly encountered in traditional algorithm. We then apply our results modeling of daily COVID-19 cases Chile.

Язык: Английский

Процитировано

3

Advanced Mathematical Approaches in Psycholinguistic Data Analysis: A Methodological Insight DOI Creative Commons
Cecília Castro, Víctor Leiva, Maria do Carmo Lourenço-Gomes

и другие.

Fractal and Fractional, Год журнала: 2023, Номер 7(9), С. 670 - 670

Опубликована: Сен. 5, 2023

In the evolving landscape of psycholinguistic research, this study addresses inherent complexities data through advanced analytical methodologies, including permutation tests, bootstrap confidence intervals, and fractile or quantile regression. The methodology philosophy our approach deeply resonate with fractal fractional concepts. Responding to skewed distributions data, which are observed in metrics such as reading times, time-to-response, time-to-submit, analysis highlights nuanced interplay between time-to-response variables like lists, conditions, plausibility. A particular focus is placed on implausible sentence response showcasing precision chosen methods. underscores profound influence individual variability, advocating for meticulous rigor handling intricate complex datasets. Drawing inspiration from mathematics, findings emphasize broader potential sophisticated mathematical tools contemporary setting a benchmark future investigations psycholinguistics related disciplines.

Язык: Английский

Процитировано

1