# Olgierd HryniewiczInstytut Badań Systemowych Polskiej Akademii Nauk | IBSPAN · Stochastic Methods

Olgierd Hryniewicz

Professor

## About

135

Publications

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810

Citations

Citations since 2017

Additional affiliations

May 2010 - present

May 1998 - May 2010

November 1992 - May 1998

## Publications

Publications (135)

Monitoring of inhomogeneous processes characterized by complex structures has been considered. The application of well-known methods of Statistical Process Control (SPC) for such processes may be questionable, as the interpretation of the results of monitoring of such complex processes using the SPC methods is difficult. In the paper, we consider p...

In this work, inspired by the interpretability and usefulness of the statistical process control, we propose a novel procedure for simultaneous monitoring of multiple processes that is based on a neural network with learnable activation functions. The proposed procedure for learning control limits with neural network (CONNF) is aimed at scenarios w...

Intelligent systems for the medical domain often require processing data streams that evolve over time and are only partially labeled. At the same time, the need for explanations is of utmost importance not only due to various regulations, but also to increase trust among systems’ users. In this work, an online data-driven learning method with focu...

We introduce an approach called PLENARY (exPlaining bLack-box modEls in Natural lAnguage thRough fuzzY linguistic summaries), which is an explainable classifier based on a data-driven predictive model. Neural learning is exploited to derive a predictive model based on two levels of labels associated with the data. Then, model explanations are deriv...

Background:
Smartphones allow for real-time monitoring of patients' behavioral activities in a naturalistic setting. These data are suggested as markers for the mental state of patients with bipolar disorder (BD).
Objective:
We assessed the relations between data collected from smartphones and the clinically rated depressive and manic symptoms t...

Online advertising campaigns are adversely affected by bot traffic. In this paper, we develop and test a method for the estimation of its share, which is necessary for the evaluation of campaign efficiency. First, we present the nature of the problem as well as the underlying business rationale. Next, we describe the essential features of Internet...

Smartphones enable to collect large data streams about phone calls that, once combined with Computational Intelligence techniques, bring great potential for improving the monitoring of patients with mental illnesses. However, the acoustic data streams recorded in uncontrolled environments are dynamically changing due to various sources of uncertain...

Baoding Liu created uncertainty theory to describe the information represented by human language. In turn, Yuhan Liu founded chance theory for modelling phenomena where both uncertainty and randomness are present. The first theory involves an uncertain measure and variable, whereas the second one introduces the notions of a chance measure and an un...

Voice features from everyday phone conversations are regarded as a sensitive digital marker of mood phases in bipolar disorder. At the same time, although acoustic data collected from smartphones are relatively large, their psychiatric labelling is usually very limited, and there is still a need for intelligent and interpretable approaches to proce...

Streams of data collected from sensors are usually large and inhomogeneous in time. In this paper, we consider the case when data consist of subsegments of different lengths governed by possibly different probability distributions. The data describing consecutive subsegments are presented in the form of histograms. Next, these subsegments are group...

The M-probability theory was introduced for intuitionistic fuzzy events (IFEs), defined by Atanassov’s intuitionistic fuzzy sets (IFSs). In this paper, we formulate and prove generalized versions of the strong law of large numbers (SLLN for short), i.e. the Brunk–Prokhorov SLLN, Marcinkiewicz–Zygmund SLLN, Korchevsky SLLN within the M-probability t...

Processes described by indirectly observed data naturally arise in applications, such as telehealth systems. The available data can be used to predict the characteristics of interest, which form a process to be monitored. Its randomness is largely related to the classification (diagnosis) errors. To minimize them, one can use ensembles of predictor...

BACKGROUND
Smartphones allow for real-time monitoring of patients’ behavioral activities in a naturalistic setting. These data are suggested as markers for the mental state of patients with bipolar disorder (BD).
OBJECTIVE
We assessed the relations between data collected from smartphones and the clinically rated depressive and manic symptoms toget...

In this paper, a new methodology for simulating bootstrap samples of fuzzy numbers is proposed. Unlike the classical bootstrap, it allows enriching a resampling scheme with values from outside the initial sample. Although a secondary sample may contain results beyond members of the primary set, they are generated smartly so that the crucial charact...

Acoustic features about phone calls are promising markers for prediction of bipolar disorder episodes. Smartphones enable collection of voice signal on a daily basis, and thus, the amount of data available for analysis is quickly growing. At the same time, even though the collected data are crisp, there is a lot of imprecision related to the extrac...

In this paper, we propose two new resampling algorithms for the simulation of bootstrap-like samples of interval-valued fuzzy numbers (IVFNs). These methods (namely, the d-method and the s-method) re-use a primary sample (an initial set) of IVFNs to generate a secondary sample, which also consists of this type of fuzzy numbers, and simultaneously u...

A new resampling approach for simulating bootstrapped samples of fuzzy numbers is proposed. The secondary samples consist of fuzzy numbers which preserve the canonical representation (i.e., the value and ambiguity) of fuzzy numbers belonging to the primary sample, although may differ from the initial ones. This way the resulting bootstrap distribut...

Monitoring the stability of processes described by autocorrelated time series requires dedicated tools such as the Shewhart control chart for residuals. This paper discusses and extends a recently introduced ensemble prediction framework for time series called weighted averaged models (WAM). Central to the WAM approach are the weights of the base a...

Many-valued (MV; the many-valued logics considered by Łukasiewicz)-algebras are algebraic systems that generalize Boolean algebras. The MV-algebraic probability theory involves the notions of the state and observable, which abstract the probability measure and the random variable, both considered in the Kolmogorov probability theory. Within the MV-...

In this paper, we propose two new nonparametric resampling methods for the simulation of bootstrap-like samples of fuzzy numbers. The generated secondary samples are based on an input set (i.e., a primary sample) consisting of left–right fuzzy numbers. The proposed approaches utilize random simulations in a way which, to some extent, resembles a bo...

Bipolar disorder (BD) is a serious mental disorder characterized by manic episodes of elevated mood and overactivity, interspersed with periods of depression. Typically, the clinical assessment of aective state is carried out by psychiatrist during routine checkup visits. However , diagnostics of a phase change can be facilitated by monitoring data...

Non-standard probability theories have been developed for modeling random systems in complex spaces, such as, e.g., quantum systems. One of these theories, the MV-algebraic probability theory, involves the notions of state and observable, which were introduced by abstracting the properties of the Kolmogorovian probability measure and the classical...

Monitoring of processes described by autocorrelated time series data has been considered. For this purpose, we propose to use the Shewhart control chart for residuals, designed using the \(WAM*\) approach introduced by the authors. The main problem, that has to be solved in the design of the proposed control chart, is the choice of the weight \(w_0...

Bipolar disorder is a mental illness affecting over 1% of the world’s population. In the course of disease there are episodic fluctuations between different mood phases, ranging from depression to manic episodes and mixed states. Early detection and treatment of prodromal symptoms of affective episode recurrence is crucial since it reduces the conv...

Control charts for monitoring residuals are the main tools for statistical process control of autocorrelated streams of data. X chart for residuals, calculated from a series of individual observations, is probably the most popular, but its statistical characteristics are not satisfactory, especially for charts designed using limited amount of data....

Bipolar disorder (BD) is a serious mental disorder characterized by manic episodes of elevated mood and overactivity, interspersed with periods of depression. Typically, the psychiatric assessment of affective state is carried out by a psychiatrist during routine check-up visits. However, diagnostics of a phase change can be facilitated by monitori...

The novelty of this research is to use linguistically quantified sentences, the so called linguistic summaries, to improve time series forecasting. The proposed Forecasting with Linguistic Summaries (F-LS) approach combines multiple autoregressive models in line with the Bayesian model averaging. However, instead of defining prior probability distr...

Control charts for monitoring residuals are the main tools for statistical process control of autocorrelated streams of data. X chart for residuals calculated from a series of individual observations is probably the most popular, but its statistical characteristics are not satisfactory, especially for charts designed using limited amount of data. I...

Interval-valued fuzzy sets were introduced in 1970s as an extension of Zadeh’s fuzzy sets. For interval-valued fuzzy events, (IV-events for short) IV-probability theory has been developed. In this paper, we prove central limit theorems for triangular arrays of IV-observables within this theory. We prove the Lindeberg CLT and the Lyapunov CLT, assum...

Many different control charts have been proposed during the last 30 years for monitoring processes with autocorrelated observations (measurements). The majority of them are developed for monitoring residuals, i.e., differences between the observed and predicted values of the monitored process. Unfortunately, statistical properties of these chart ar...

Selection of an appropriate time series model and estimation of its parameters may become very challenging tasks for short series of observations. The state-of-the-art information criteria often fail to adequately identify the predictive model for the small sample sizes, for which real-life applications are routinely made. Within this research, we...

In the paper we
have considered different approaches for the calculation of the p-value for fuzzy statistical tests. For the particular problem of testing hypotheses about the mean in the normal distribution with known standard deviation, and a certain type of fuzziness (both in data and tested hypotheses) we have found probability distributions of...

The Paris-Erdogan equation is one of the most widely accepted fatigue crack growth equations. Apart from its classical version, its randomized form was considered by Sobczyk and Spencer. In this paper we study the stochastic Paris-Erdogan model with white noise in the Itô interpretation in fuzzy framework. We assume that the model parameters cannot...

Although time series analysis and forecasting have been studied since the seventeenth century and the literature related to its statistical foundations is extensive, the problem arises when the assumptions underlying statistical modeling are not fulfilled due to the shortness of available data. In such cases, additional expert knowledge is needed t...

This paper provides a comprehensive analysis of computational problems concerning calculation of general correlation coefficients for interval data. Exact algorithms solving this task have unacceptable computational complexity for larger samples, therefore we concentrate on computational problems arising in approximate algorithms. General correlati...

SPC procedures for process inspection by attributes are usually designed under the assumption of directly observed quality data. However, in many practical cases this direct observations are very costly or even hardly possible. For example, in the production of pharmaceuticals costly and time consuming chemical analyses are required for the determi...

MV-algebras can be treated as non-commutative generalizations of boolean algebras. The probability theory of MV-algebras was developed as a generalization of the boolean algebraic probability theory. For both theories the notions of state and observable were introduced by abstracting the properties of the Kolmogorov's probability measure and the cl...

In the majority of decision models used in practice all input data are assumed to be precise. This assumption is made both for random results of measurements, and for constant parameters such as, e.g. costs related to decisions. In reality many of these values are reported in an imprecise way. When this imprecision cannot be related to randomness t...

Bayesian methods are widely accepted as the methodology for the analysis of reliability data. In practical applications such data are often expressed in an imprecise way. In such a case fuzzy sets are frequently used for modeling imprecision. In the paper we present some recent results on the application of the fuzzy Bayes methodology for the analy...

Soft computing techniques may provide various forms of human-consistent summaries about large time series databases, e.g., linguistic summaries, frequent patterns, fuzzy IF-THEN rules. Within this research, we focus on linguistic summaries constructed as linguistically quantified propositions, that may be exemplified by 'Among all increasing trends...

In this paper, we consider a nonparametric Shewhart chart for fuzzy data. We utilize the fuzzy data without transforming them into a real-valued scalar (a representative value). Usually fuzzy data (described by fuzzy random variables) do not have a distributional model available, and also the size of the fuzzy sample data is small. Based on the boo...

Finding an appropriate predictive model for time series and formulating its assumptions may become very challenging task. We propose to represent time series in a human-consistent way using linguistic summaries. Such summaries describe general trends in time series and are easily interpretable for decision makers. The aim of this contribution is to...

As observed in a real-life production company, there is often a need to forecast demand for new products, despite the shortness of the available time series data. We introduce an innovative approach to discover prior information from experts in their fields and incorporate this into the bayesian autoregressive forecasting. It is observed that for t...

Fuzzy random variables are used when randomness is merged with imprecision described by fuzzy sets. When we need to use computer simulations for the comparison of a classical probabilistic approach with that based on fuzzy random variables we need to establish the method for the generation of crisp random variables compatible with existing fuzzy da...

SPC
procedures are usually designed to control stability of directly observed parameters of a process. However, when quality parameters of interest are related to reliability characteristics it is practically hardly possible to monitor such characteristics directly. Instead, we use some training data in order to build a model that is used for the p...

Glossary
Definition of the Subject
Introduction
Mathematical Modeling of Imprecise Data
Fuzzy Random Variables
Statistical Analysis of Fuzzy Data Corresponding to Fuzzy Perceptions of Existing Real–Valued Data
Statistical Analysis of Existing Fuzzy-Valued Data
Future Directions
Bibliography

A direct comparison among highly uncertain inventories of emissions is inadequate and may lead to paradoxes. This issue is of particular importance in the case of greenhouse gases. This paper reviews the methods for the comparison of uncertain inventories in the context of compliance checking. The problem is treated as a comparison of uncertain alt...

Pearson's coefficient of linear correlation r is the measure of dependence which is the most popular among practitioners. In the paper we have shown, using comprehensive computer simulations, that its application is very limited when we search for informative variables that can be used for the prediction of reliability. We have shown that Kendall's...

In recent years there has been a growing interest to extend classical methods for data analysis. The aim is to allow a more flexible modeling of phenomena such as uncertainty, imprecision or ignorance. Such extensions of classical probability theory and statistics are useful in many real-life situations, since uncertainties in data are not only pre...

Experts are able to predict sales based on approximate reasoning and subjective beliefs related to market trends in general but also to imprecise linguistic concepts about time series evolution. Linguistic concepts are linked with demand and supply, but their dependencies are difficult to be captured via traditional methods for crisp data analysis....

Calculation of the strength of dependence in the case of interval data is computation-wise a very demanding task. We consider the case of Kendall’s τ statistic, and calculate approximations of its minimal and maximal values using very easy to compute heuristic approximations. Using Monte Carlo simulations and more accurate calculations based on an...

In the paper we consider the problem of the statistical evaluation and comparison of different classification algorithms. For this purpose we apply the methodology of statistical tests for testing independence in the case the multinomial distribution. We propose to use two-sample tests for the comparison of different classification algorithms. In t...

Long-lasting exploitation of a machine usually brings about wear and tear of its subsystems due to deteriorated material properties and mechanical wearing, which means that all safety functions should be periodically inspected for finding any changes in parameter values that could reduce the control system capability to perform its function. Theref...

The paper deals with the problem of choosing an appropriate inspection interval for monitoring of safety related control systems in machinery. Extremely simple approximate models have been proposed in order to provide practitioners without reliability training useful tools for the determination of inspection policies. These methods allow practition...

Shewhart control charts were originally designed under the assumption of independence of consecutive observations. In the presence of dependence the authors usually assume dependencies in the form of autocorrelated and normally distributed data. However, there exist many other types of dependencies which are described by other mathematical models....

In the majority of decision models used in practice all input data are assumed to be precise. This assumption is made both for random results of measurements, and for constant parameters such as, e.g. costs related to decisions. In reality many of these values are reported in an imprecise way. When this imprecision cannot be related to randomness t...

In the paper we consider the problem of the evaluation and comparison of different classification algorithms. For this purpose we apply the methodology of statistical tests for the multinomial distribution. We propose to use two-sample tests for the comparison of different classification algorithms, and one-sample goodness-of-fit tests for the eval...

In many practical applications of statistics it is assumed that the observed realizations of measurements are mutually independent.
This assumption is usually made in order to ease necessary computations. However, for real data sets, especially large ones,
the application of statistical tests of independence very often leads to the rejection of the...

The existence of dependencies between consecutive observations of a process makes the usage of SPC tools much more complicated. In order to avoid unnecessary costs we need to have simple tools for the discrimination between correlated and uncorrelated process data. In the paper we propose a new control chart based on Kendall's tau statistic which c...

The paper deals with the problem of the mathematical description of uncertainties of different type. It has been demonstrated
by many authors that the theory of probability is not always suitable for the description of uncertainty related to vagueness.
We briefly present some of the most promising theories which have been recently proposed for copi...

The paper presents a new methodology for making statistical decisions when data is reported in an imprecise way. Such situations happen very frequently when quality features are evaluated by humans. We have demonstrated that traditional models based either on the multinomial distribution or on predefined linguistic variables may be insufficient for...

Selected papers from the 4th International Conference on Soft Methods in Probability and Statistics, SMPS 2008, Toulouse, France, September 8-10, 2008

Probability theory has been the only well-founded theory of uncertainty for a long time. It was viewed either as a powerful tool for modelling random phenomena, or as a rational approach to the notion of degree of belief. During the last thirty years, in areas centered around decision theory, artificial intelligence and information processing, nume...

In contrast to laboratory lifetime tests reliability field tests are usually performed in conditions which vary in time in a random way. We consider the case when users are asked about their description of their vague perceptions of the usage conditions. In the paper we use interval-valued variables for the description of imprecisely known test con...

Reliability sampling is a part of acceptance sampling dedicated to the control of those quality characteristics of a product, which are related to its functioning in time. Therefore, in reliability sampling we are interested in such quality characteristics of a product as: mean time to failure (MTTF), mean time between failures (MTBF), probability...

Statistical quality control (SQC) is an important field where both theory of probability and theory of fuzzy sets may be used.
In the paper we give a short overview of basic problems of SQC that have been solved using both these theories simultaneously.
Some new results on the applications of fuzzy sets in SQC are presented in details. We also pres...

Kendall’s τ statistic has found many practical applications. Recently, it has been proposed by Hryniewicz and Szediw as the basis for the Kendall control chart for monitoring autocorrelated production processes. They have shown that this chart has good statistical characteristics only for large samples. Unfortunately, in such a case existing algori...

In contrast to laboratory lifetime tests reliability field tests are usually performed in conditions which vary in time in a random way. We consider the case when users are asked about their description of their vague perceptions of the usage conditions. In the paper we use interval-valued variables for the description of imprecisely known test con...

The paper presents a new approach to the analysis of the greenhouse gases inventories. For the evalua- tion of the greenhouse gases emis- sion we propose to use a fuzzy- random model. This model enables us to discriminate between dierent sources of uncertainty in estimates of emission inventories. The pro- posed model can be used for a more adequat...

Increased competition on the global market forces producers to follow policies leading to finite production runs. This situation requires implementation of a new type of inspection procedures with the aim to improve or sustain production quality levels. One of the most important aspects in the design of inspection processes is the specification of...

Theory of reliability is more than fifty years old. Its basic concepts were established in the 1950s as useful tools for the analysis of complex technical systems. The rapid development of the theory of reliability was closely related to the importance of its main field of applications - military and space. For this reason the origins of the resear...

In the paper we propose a very simple method for the analysis of dependencies between consecutive observations of a short
time series when individual observations are imprecise (fuzzy). For this purpose we propose to apply a fuzzy version of the
Kendall’s τ statistic. The proposed methodology can be used for the analysis of a short series of opinio...

Książka ta jest poświęcona problemom badawczym i praktycznym z zakresu informatycznego wspomagania procesów decyzyjnych oraz sterowania w złożonych systemach technicznych, ekonomiczno-społecznych i biologicznych. Zakres tematów rozpatrywanych w ramach badań systemowych jest bardzo szeroki. Opisanie ich wszystkich jest po prostu niemożliwe. Pewnym r...

The generalisation of the Goodman–Kruskal γ statistic that is used for the measurement of the strength of dependence (association) between two categorical variables with ordered categories is presented. The case when some data are not precise, and observations are described by possibility distributions over a set of categories of one variable is co...

The paper deals with the problem of the interpretation of the results of statistical tests in terms of the theory of possibility. The well known concept in statistics of the observed test size p (also known as p-value and significance) has been given a new possibilistic interpretation and generalised for the case of imprecisely defined statistical...

Solving complex decision problems requires the usage of information from different sources. Usually this information is uncertain
and statistical or probabilistic methods are needed for its processing. However, in many cases a decision maker faces not
only uncertainty of a random nature but also imprecision in the description of input data that is...

In this paper, we consider the problem of the evaluation of system reliability using statistical data obtained from reliability
tests of its elements, in which the lifetimes of elements are described using an exponential distribution. We assume that
this lifetime data may be reported imprecisely and that this lack of precision may be described usin...

Statistical analysis of dependencies existing in data sets is now one of the most important applications of statistics. It
is also a core part of data mining - a rapidly developing in recent years part of information technology. Statistical methods
that have been proposed for the analysis of dependencies in data sets can be roughly divided into two...