A New Technique of Intelligent Constructing Unbiased Prediction Limits on Future Order Statistics Coming from an Inverse Gaussian Distribution under Parametric Uncertainty

Nechval, Nicholas A.; Berzins, Gundars; Nechval, Konstantin N.; Krasts, Juris

doi:10.3103/s0146411619030088

Cited by 16 publications

(4 citation statements)

References 23 publications

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“…The factor analysis method is an analysis method developed on the basis of principal component analysis, and its main target of study is the degree of connection within the matrix, that is, taking the matrix with the original index data as the basis, studying the internal structure of this matrix, and then searching for independent new factors that have a dominant effect on this structure so as to locate those particular factors that can influence the variables. The purpose of factor analysis is not to find the main factors [ 19 , 20 ] but to know what these factors stand for. But the principal component analysis method finds the initial loading matrix of the solution of the principal factor that does not satisfy the simple structure principle and the typical variables represented by each factor are not very prominent, thus leading to ambiguity in the meaning of the factors.…”

Section: Related Workmentioning

confidence: 99%

Correlation between the Quality of Talent Training and Regional Economic Development Based on Multivariate Statistical Analysis Model

Yuan

2022

Applied Bionics and Biomechanics

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Entering the era of knowledge economy, the economic value of talent education is more and more emphasized, and it contributes more and more to the local economy and injects new vitality into local economic development. However, there are still some difficulties in the synergistic development of talent education and local economy, such as the low degree of integration of “industry, profession, and employment” and the lack of synergy between schools and enterprises, which affects the high-quality development of talent education and restricts the long-term development of regional economy. This paper incorporates machine learning algorithms to construct a multivariate statistics analysis model based on the correlation analysis model between talent training quality and regional economic development. Based on the multi-variate statistical analysis theory and method, the qualitative analysis and quantitative analysis are closely combined to scientifically pick up the main indicators affecting the comprehensive quality of talent cultivation and overcome the drawbacks of artificial subjective assignment of values. Through the judicious selection of evaluation indexes, a scientific and fair evaluation model is established, and the targets of talent cultivation are combined with regional economic development, in a comprehensive analysis, which provides a new means for the development of the regional economy.

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Section: Related Workmentioning

confidence: 99%

Correlation between the Quality of Talent Training and Regional Economic Development Based on Multivariate Statistical Analysis Model

Yuan

2022

Applied Bionics and Biomechanics

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“…In order to exclude the unknown (nuisance) parameter δ from (116), we use the technique of invariant statistical embedding and averaging in terms of pivotal quantities (ISE&APQ) [3][4][5][6][7][8][9][10][11][12] as follows. We reduce (116) to Then (132) can be transformed to cumulative distribution function (CDF) of (1) Y as follows:…”

Section: Finding the Mle Of β And δ And Adequate Probability Distribumentioning

confidence: 99%

“…79)Classical approach to solving the problem. It follows from(8) and (76) that this example, version 1 is an adequate version of possible decision making. Optimal analytical solution.…”

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confidence: 95%

A New Unified Computational Approach to Intelligent Constructing Shortest-Length or Equal Tails Confidence Intervals under Parametric Uncertainty

Nechval¹,

Berzins²,

Nechval³

et al. 2020

JAMC

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“…Guenther [7] and Hahn and Meeker [8] discuss how one-sided tolerance limits can be used to obtain approximate two-sided tolerance intervals by applying Bonferroni's inequality. In Nechval et al [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26], the exact statistical tolerance and prediction limits are discussed under parametric uncertainty of underlying models.…”

Section: Introductionmentioning

confidence: 99%

A Novel Intelligent Technique of Invariant Statistical Embedding and Averaging via Pivotal Quantities for Optimization or Improvement of Statistical Decision Rules under Parametric Uncertainty

Nechval

Berzins

Nechval

2020

Wseas Transactions on Mathematics

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In the present paper, for intelligent constructing efficient (optimal, uniformly non-dominated, unbiased, improved) statistical decisions under parametric uncertainty, a new technique of invariant embedding of sample statistics in a decision criterion and averaging this criterion over pivots’ probability distributions is proposed. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, the technique of invariant statistical embedding and averaging via pivotal quantities (ISE&APQ) is independent of the choice of priors and represents a novelty in the theory of statistical decisions. It allows one to eliminate unknown parameters from the problem and to find the efficient statistical decision rules, which often have smaller risk than any of the well-known decision rules. The aim of the present paper is to show how the technique of ISE&APQ may be employed in the particular case of optimization, estimation, or improvement of statistical decisions under parametric uncertainty. To illustrate the proposed technique of ISE&APQ, illustrative examples of intelligent constructing exact statistical tolerance limits for prediction of future outcomes coming from log-location-scale distributions under parametric uncertainty are given

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A New Technique of Intelligent Constructing Unbiased Prediction Limits on Future Order Statistics Coming from an Inverse Gaussian Distribution under Parametric Uncertainty

Cited by 16 publications

References 23 publications

Correlation between the Quality of Talent Training and Regional Economic Development Based on Multivariate Statistical Analysis Model

Correlation between the Quality of Talent Training and Regional Economic Development Based on Multivariate Statistical Analysis Model

A New Unified Computational Approach to Intelligent Constructing Shortest-Length or Equal Tails Confidence Intervals under Parametric Uncertainty

A Novel Intelligent Technique of Invariant Statistical Embedding and Averaging via Pivotal Quantities for Optimization or Improvement of Statistical Decision Rules under Parametric Uncertainty

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