A New Simple Computational Method of Simultaneous Constructing and Comparing Confidence Intervals of Shortest Length and Equal Tails for Making Efficient Decisions Under Parametric Uncertainty

A confidence interval is a range of values that provides the user with useful information about how accurately a statistic estimates a parameter. In the present paper, a new simple computational method is proposed for simultaneous constructing and comparing confidence intervals of shortest length and equal tails in order to make efficient decisions under parametric uncertainty. This unified computational method provides intervals in several situations that previously required separate analysis using more advanced methods and tables for numerical solutions. In contrast to the Bayesian approach, the proposed approach does not depend on the choice of priors and is a novelty in the theory of st…

Prototype proposal for profiling and identification of tv viewers using watching patterns

A Novel Intelligent Technique for Product Acceptance Process Optimization on the Basis of Misclassification Probability in the Case of Log-Location-Scale Distributions

In this paper, to determine the optimal parameters of the product acceptance process under parametric uncertainty of underlying models, a new intelligent technique for optimization of product acceptance process on the basis of misclassification probability is proposed. It allows one to take into account all possible situations that may occur when it is necessary to optimize the product acceptance process. The technique is based on the pivotal quantity averaging approach (PQAA) which allows one to eliminate the unknown parameters from the problem and to use available statistical information as completely as possible. It is conceptually simple and easy to use. One of the most important featur…

Huff model for shopping centre assessment using aggregated mobile phone data

Decision Making and Optimization for Inspection Planning under Parametric Uncertainty of Underlying Models

Certain fatigued structures must be inspected in order to detect fatigue damages that would otherwise not be apparent. A technique for obtaining optimal inspection strategies is proposed for situations where it is difficult to quantify the costs associated with inspections and undetected failure. For fatigued structures, for which failures (fatigue damages) are only detected at the time of inspection, it is important to be able to determine the optimal times of inspection. Fewer inspections will lead to lower fatigue reliability of the structure upon demand, and frequent inspections will lead to higher cost. When there is a fatigue reliability requirement, the problem is usually to develop …

A New Technique for Education Process Optimization via the Dual Control Approach

A New Intelligent Technique of Constructing Optimal Airline Seat Protection Levels for Multiple Nested Fare Classes of Single-Leg Flights

A new, rigorous formulation of the optimization problem of airline seat protection levels for multiple nested fare classes is presented. A number of results useful for practical application are obtained. A numerical example is given.

A New Dynamic Model for Anticipatory Adaptive Control of Airline Seat Reservation via Order Statistics of Cumulative Customer Demand

This paper deals with dynamic anticipatory adaptive control of airline seat reservation for the stochastic customer demand that occurs over time T before the flight is scheduled to depart. It is assumed that time T is divided into m periods, namely a full fare period and m−1 discounted fare periods. The fare structure is given. An airplane has a seat capacity of U. For the sake of simplicity, but without loss of generality, we consider (for illustration) the case of nonstop flight with two fare classes (business and economy). The proposed policies of the airline seat inventory control are based on the use of order statistics of cumulative customer demand, which have such properties as bivar…

Prediction Model Selection and Spare Parts Ordering Policy for Efficient Support of Maintenance and Repair of Equipment

The prediction model selection problem via variable subset selection is one of the most pervasive model selection problems in statistical applications. Often referred to as the problem of subset selection, it arises when one wants to model the relationship between a variable of interest and a subset of potential explanatory variables or predictors, but there is uncertainty about which subset to use. Several papers have dealt with various aspects of the problem but it appears that the typical regression user has not benefited appreciably. One reason for the lack of resolution of the problem is the fact that it has not been well defined. Indeed, it is apparent that there is not a single probl…

Use and development of contingency theory

There is no universal way to manage an organization. Contingency theory helps to develop organization’s design using subsystems in combination with an environment. The present article analyses development of contingency theory since 1998. The study used componential and document analysis method - study was made based on semantic approach using publications in scientific journals included in Web of Science or Scopus database; publications were manually selected. One research proposition was developed to focus the study, it claimed – contingency theory continues to be used to analyse specific situational factors. Our research study showed that contingency theory during last 20 years was affec…

Adaptive Planning in-Service Inspections of Fatigued Structures in Damage Tolerance Situations via Observations of Crack Growth Process

From an engineering standpoint the fatigue life of a fatigued structure consists of two periods: (i) crack initiation period, which starts with the first load cycle and ends when a technically detectable crack is presented, and (ii) crack propagation period, which starts with a technically detectable crack and ends when the remaining cross section can no longer withstand the loads applied and fails statically. The main aim of this paper is to present more accurate innovative stochastic fatigue model for adaptive planning inspections of fatigued structures in damage tolerance situations via observations of crack growth process during a crack propagation period. A new crack growth equation is…

Mobile Phone Data Statistics as Proxy Indicator for Regional Economic Activity Assessment

The mobile data analysis is an authoritative source of information for problems solving in the fields of human activity recognition, population dynamics, tourism, transport planning, traffics measuring, public administration and other activities and could be the source for valuable information as a proxy indicator. One of the obstacles to user data from mobile operators is compliance to the General Data Protection Regulation, so the development of data analytics approach that protects personal data without a necessity to identify mobility of particular persons was developed, that still provides economically relevant data. In the present research, the method for the economic activity assessm…

Mobile phone data statistics as a dynamic proxy indicator in assessing regional economic activity and human commuting patterns

Pattern Identification by Factor Analysis for Regions with Similar Economic Activity Based on Mobile Communication Data

The study analyses the regions’ economic activity in Latvia using Latvia Mobile Telephone (LMT) mobile communication data from July 2015 to January 2017. The call activity and a number of unique phone users by 119 Latvia counties and biggest cities were analysed in two steps: at first method of principal components was used to explain the variance in the data and then exploratory factor analysis was applied. Three factors were identified that describe 87.5% of the total variance of the aggregated daily data. The first factor is related more to the regions with higher economic activity, the second and third factors capture, respectively, lowers call activity during weekdays and are related t…

Invariant Embedding Technique and Its Applications for Improvement or Optimization of Statistical Decisions

In the present paper, for improvement or optimization of statistical decisions under parametric uncertainty, a new technique of invariant embedding of sample statistics in a performance index 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, an invariant embedding technique is independent of the choice of priors. It allows one to eliminate unknown parameters from the problem and to find the best invariant decision rule, which has smaller risk than any of the well-known decision rules. To illustrate the proposed technique, applica…

Development of Waste Collection Model Using Mobile Phone Data: A Case Study in Latvia

In organizing household waste management and controlling waste collection and disposal, it is necessary to minimise risks to the environment and human health and, where possible, ensure that waste is recycled and returned to the economic cycle. Different models are being applied to increase waste collection management efficiency, but in recent years, the mobile phone data is widely used to solve various application problems. The research objective is to develop a waste collection model, which responds to the population’s current demands and allows planning waste container loading, based on mobile phone data statistics. The developed approach, techniques and data model can be used for waste …

Improvement of Statistical Decisions under Parametric Uncertainty

A large number of problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncertainty. Decision‐making under uncertainty is a central problem in statistical inference, and has been formally studied in virtually all approaches to inference. The aim of the present paper is to show how the invariant embedding technique, the idea of which belongs to the authors, may be employed in the particular case of finding the improved statistical decisions under parametric uncertainty. This technique represents a simple and computationally attractive statistical method based on the constructive use of the i…

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

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 i…

Population Mobility Patterns and Monitoring of COVID-19 Restriction Measures in Latvia