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Research in Statistics
Scopus
ISSN 2768-4520 · Taylor & Francis · 78 artikel di indeks
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Artikel Jurnal
Mitigating multicollinearity in ridge regression: a comparative study of quantile-based two parameter weighted KL-estimators
In linear regression, when predictors exhibit collinearity, the problem of multicollinearity arises, leading to a reduction in the efficiency of the ordinary least squares (OLS) estimator. In this paper, we develop quantile-based two-parameter ridge weighted Kibria-Lukman (QTPRKL) estimators to…
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A novel approach to forecast time series exhibiting aperiodic cycles using Exponential Autoregressive Moving Average models
When modeling real-world processes, the data generating process may exhibit behavior such as significant aperiodic cycles with variable peaks and troughs. In such cases, which can be ascertained through periodogram analysis, non-linear time-series models are crucial. Evolved from the family of…
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Gofedf: an R package for testing goodness-of-fit tests based on the empirical distribution function
We introduce an R package for goodness-of-fit testing based on the empirical distribution function (EDF) in the presence of parameter estimation, which can be applied to any general likelihood model. The computation of the p value in goodness-of-fit tests based on EDF with parameter estimation…
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Maximization of the two-parameter multivariate normal likelihood avoiding logarithm and differentiation
We consider the classical problem of maximizing the likelihood function of the mean vector and the dispersion matrix given a sample from the family of multivariate Normal distributions. While the solution to the problem is extremely well known, all the existing methods of obtaining the solution are…
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The effect on fit measures of model misspecification when there is a planned pattern of missingness
This research aims to assess the sensitivity of the typical fit measures, specifically the root mean square error of approximation, standardized root mean square residual, comparative fit index, and Tucker-Lewis index, in the adjustment of misspecified structural equation models when there is a…
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Volatility-resilient cryptocurrency forecasting using deep temporal models and metaheuristic optimization
This paper presents a hybrid deep learning framework for cryptocurrency price forecasting that integrates complementary modeling, feature selection, and optimization techniques to address the volatility and nonstationarity of financial time series. The framework combines Convolutional Neural…
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Veracity evaluation of ChatGPT’s mathematical solutions via M-polar fuzzy graphs
This study evaluates ChatGPT’s reliability in solving mathematics problems, with a focus on using m-polar fuzzy graphs for decision-making. While ChatGPT performs well in elementary arithmetic and logic, its accuracy decreases as problem complexity increases. To analyze this, we applied graph…
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On the T-Topp-Leone family of distributions for lifetime data analysis
This study introduces a new family of distributions based on the [Formula: see text] framework by employing the Topp–Leone distribution as a generator. The resulting [Formula: see text] family is developed, and three subclasses are obtained using the exponential, Weibull, and log-normal…
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Identifying learner profiles for pre-award research funding activities in Universities of Applied Sciences: a multivariate approach
This paper presents findings from the European-funded ENCARE project, which aims to strengthen the capacity of staff at the Universities of Applied Sciences (UAS) in Europe to secure European Union (EU) research funding. Six UAS from different countries collaborated to design a capacity-building…
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Integration of mixed scale measurement model on intervening exogenous and endogenous variables with path analysis (study on child stunting prevention)
This study addresses the challenge of analyzing mixed-scale data, particularly in stunting research, where variables are measured on different scales and may exhibit nonlinear relationships. This study aims to integrate mixed-scale Principal Component Analysis (PCA) measurement models on exogenous…
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Discrete interval probability distribution of a coarse-grained Poisson process
The Poisson process is a stochastic process characterized by exponentially distributed time intervals between events, or equivalently, the number of events occurring within a fixed time interval follows a Poisson distribution. However, the exponential distribution of event intervals is based on the…
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Optimal measurement to characterize tumor growth for personalized intervention
Treatment efficacy in tumor shrinkage in in-vivo experimental oncology depends not only on the therapeutic intervention but also on the underlying tumor growth dynamics. Consequently, precise and accurate estimation of the model parameters governing individual tumor volume is essential, as is the…
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Confidence interval and test for the mean of a zero-inflated two-parameter negative binomial distribution
Zero-inflated over-dispersed count data arise in many applications, motivating the zero-inflated negative binomial family. We develop likelihood-based inference for the negative binomial two-parameter (NB2) component mean [Formula: see text] under a zero-inflated two-parameter negative binomial…
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A stochastic assessment of monthly rainfall pattern: a case of Owerri, Nigeria
This study addresses a critical gap in agro-meteorological planning: the absence of reliable probabilistic models for predicting monthly rainfall regimes. Specifically, we aim to quantify the long-term distribution of dry, wet, and rainy months in Owerri, Imo State, Nigeria, using a three-state…
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Positioning personal polygenic risk score against the population background
Polygenic risk scores, or PRS, have been widely used across many traits to estimate polygenic risk, pleiotropy, and disease prediction. While PRS has the potential to be simple and informative they are not generally interpretable and not directly comparable between studies. They depend on the…
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A comparative study of Cox proportional hazards and parametric survival models using residual diagnostics and shrinkage estimation
Parametric regression models allow for comparison with the widely used Cox proportional hazards model in survival analysis, yet they remain underutilized in practice. While the Cox model is well regarded for its minimal distributional assumptions, fully parametric models can provide meaningful…
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Many-to-one comparisons with general linear model in the presence of missing observations
This study proposes a new parametric Dunnett-type procedure for many-to-one comparisons with general linear models (GLM) in the presence of missing observations. The procedure pools GLM results from multiple imputed datasets, accounting for the multiplicity inherent in many-to-one comparisons. The…
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Statistical inference based on score functions of distribution
In recent decades, a number of articles have appeared expanding and applying the basic framework of Stein’s method for estimating parameters by minimizing the distance between the score function of the data and of the model. The score function of distribution (the sfd function) is actually the…
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A new variance estimation in natural exponential families
This article focuses on improving the estimation of population variances for natural exponential family distributions, drawing inspiration from the innovative idea presented by Stein. The estimation is based on utilizing sample information on kurtosis. We derive the general form of the shrinkage…
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Hazard functions for the gamma-order generalized distributions
The target of this article is to evaluate the hazard function for the γ-order distributions, already proposed. As the γ-order Normal distribution acts as a mother distribution for the γ-order: Lognormal, Chi-square, Rayleigh, and Maxwell-Boltzmann, we evaluated and studied the hazard functions for…