Variants Of Uncertainty Research Articles

Certainty about uncertainty in sleep staging: a theoretical framework.

Sleep stage classification is an important tool for the diagnosis of sleep disorders. Because sleep staging has such a high impact on clinical outcome, it is important that it is done reliably. However, it is known that uncertainty exists in both expert scorers and automated models. On average, the agreement between human scorers is only 82.6%. In this study, we provide a theoretical framework to facilitate discussion and further analyses of uncertainty in sleep staging. To this end, we introduce two variants of uncertainty, known from statistics and the machine learning community: aleatoric and epistemic uncertainty. We discuss what these types of uncertainties are, why the distinction is useful, where they arise from in sleep staging, and provide recommendations on how this framework can improve sleep staging in the future.

Do people really prefer verbal probabilities?

When people communicate uncertainty, do they prefer to use words (e.g., "a chance", "possible") or numbers (e.g., "20%", "a 1 in 2 chance")? To answer this question, past research drew from a range of methodologies, yet failed to provide a clear-cut answer. Building on a review of existing methodologies, theoretical accounts and empirical findings, we tested the hypothesis that the preference for a particular format is driven by the variant of uncertainty that people experience. We expected that epistemic uncertainty would be more often communicated in words, whereas distributional uncertainty would be more often communicated in numbers; for the dispositional uncertainty, we expected that an individual's disposition would be more often communicated in words, whereas dispositions from the world would be more often communicated numerically. In three experiments (one oral, two written), participants communicated their uncertainty regarding two outcomes per variants of uncertainty: epistemic, dispositional and distributional. Overall, participants communicated their uncertainty more often in words, but this preference depended on the variants of uncertainty. Participants conveyed their epistemic and dispositional uncertainties more often in words and their distributional uncertainty in numbers (Experiments 1 and 2) but this effect was greatly reduced when the precision of uncertainty was held constant (Experiment 3), pointing out the key role of uncertainty vagueness. We have reviewed the implications of our findings for the existing accounts of format preferences.

Different Varieties of Uncertainty in Human Decision-Making

The study of uncertainty in decision-making is receiving greater attention in the fields of cognitive and computational neuroscience. Several lines of evidence are beginning to elucidate different variants of uncertainty. Particularly, risk, ambiguity, and expected and unexpected forms of uncertainty are well articulated in the literature. In this article we review both empirical and theoretical evidence arguing for the potential distinction between three forms of uncertainty; expected uncertainty, unexpected uncertainty, and volatility. Particular attention will be devoted to exploring the distinction between unexpected uncertainty and volatility which has been less appreciated in the literature. This includes evidence mainly from neuroimaging, neuromodulation, and electrophysiological studies. We further address the possible differentiation of cognitive control mechanisms used to deal with these forms of uncertainty. Finally, we explore whether the dual modes of control theory provides a theoretical framework for understanding the distinction between unexpected uncertainty and volatility.

Variants of uncertainty in time structure of decision making.

Variants of uncertainty in time structure of decision making.

More for Less: An Introduction to New Ideas in Mathematics, Physics and Economics

This paper introduces ideas covered at greater length and in greater depth in the following three volumes: New results on prime numbers: There is such a thing as society and: More for Less. Among ideas which it introduces are: i) a new approach to the generation of integers; ii) the idea of a mathematical-physical dichotomy and its usefulness for describing and understanding mathematical and physical and economic phenomena and; iii) fundamental roles for the ideas of duality and intervening duality in representing and explaining mathematical and physical and economic phenomena. Specifically: Sections 2 through 6 of the paper establish how abstract mathematical and physical principles can usefully be founded on a new way of motivating the generation of integers stemming from more-for-less principles together with principles of mathematical/physical dichotomy and of duality. In those five sections it is also shown how, at the same level of abstraction, such principles may be useful in exploring economic phenomena as well as more narrowly mathematical and physical phenomena. The paper then proceeds, in Sections 7 and 8, to consider foundational issues with reference to mathematics and to physics and to economics. In particular, in Section 8 much attention is given to demonstrating how and why formalizations of economic processes of interaction between individuals necessarily involve variants of uncertainty and incompleteness principles which differ in fundamental ways from those which have been considered to be important for more narrowly mathematical and physical investigations. Following an Overview the contents of the paper are: 2. More for Less An Economic Example:A Physical Example; A Mathematical Example; 3. More for less and the generation of integers; 4. More for less, contradiction and mathematical/physical dichotomy; 5. More for less and price related economic interpretations; 6. Mutual exclusion and incompleteness, orthogonality and duality; 7. Some important methodological points; 8. Some important applications to economic methodology; 9. An overall summary and some remarks concerning purposive indeterminacy, purposive incompleteness and purposive (self) contradiction. Appendix 1. Contradiction, self contradiction and collective choice: new directions for commodities and characteristics analysis. Appendix 2 Intervening duality, degeneracy and cycling via the question z=1? Appendix 3. Degeneracy, alternate optima and cycling.

Variants of uncertainty in decision-making and their neural correlates

When leaving the tidy world of rules and people start judging probabilities on an intuitive basis, it revealed that they have some intuitions to choose from. One could refer to them as a family of subjective probability concepts or following Kahneman and Tversky, as variants of uncertainty. The authors distinguished between external and internal attributions of uncertainty and could show that the perceived reason of uncertainty determines the selected coping strategy. To investigate whether variants of uncertainty can also be distinguished on the cerebral level, two functional magnetic resonance imaging studies were conducted. Participants had to predict events (abstract visual stimuli) under parametrically varying degrees of (un-)certainty. In the first experiment, uncertainty was induced by the manipulation of event probability (externally attributed uncertainty). In the second experiment, uncertainty depended on participants’ knowledge of valid rules of event occurrence, as trained before the experimental session (internally attributed uncertainty). As a result, parametric analyses revealed that activation within the posterior fronto-median cortex, particularly within mesial Brodmann area (BA) 8, increased with increasing uncertainty, no matter for which reason uncertainty emerged. Furthermore, it was found that different variants of uncertainty entailing different coping strategies can be dissociated due to additionally activated networks. Concluding, increasing activation within mesial BA 8 reflects that we are uncertain, additional networks what we do to resolve uncertainty in order to achieve future rewards. Hence, the phenomenological distinction between processes related to externally and internally attributed uncertainty is paralleled on the cerebral level.

Forecasting in Macroeconomics: A Practitioner's View

Statistical criteria for forecast quality in practice have limited relevance. They can be valid only in the context of a set of untested assumptions which are usually unknown and certainly difficult to judge for the client. Three non-statistical criteria are stressed: logical coherence, economic coherence, and stability. These criteria are best served by the use of structural models. As loss functions are usually unknown and certainty equivalence is unlikely to prevail, a forecaster must enable his client to form his opinion on the uncertainty associated with the forecast. To this end, uncertainty variants and alternative scenarios appear adequate. The robustness and flexibility of policy choices should be tested against different scenarios.

Structures and Methods of Stochastic Optimal Control Under Uncertainty

In this paper we expose the problem of stochastic optimal control in complex systems at different variants of uncertainty.

Uncertainty variants of population forecasts

"When using population forecasts it is important to take into account the degree of uncertainty of the results. For that reason the Netherlands Central Bureau of Statistics publishes low and high variants next to the most probable medium variant.... The width of the interval between the variants is based on an analysis of previous forecast errors. The degree of uncertainty of the various forecast results turns out to vary strongly.... On the basis of a statistical time-series model of forecast errors of total population growth, a confidence interval of total population size can be estimated."

THE UNPREDICTABILITY OF POPULATION TRENDS

ABSTRACT Population developments are inherently unpredictable, even for a period of a few years. Therefore, in order to produce the necessary demographic numbers, the notion of a “forecast” is often used. But official population forecasts rely on deterministic models, that cannot quantify uncertainty. This paper discusses methods to deal with uncertainty in current population forecasting. Sources of uncertainty are identified, and the role of variant forecasts is discussed: alternative futures or uncertainty variants? We treat the issue of growing uncertainty with increasing forecasting horizon: forecast or mere projection? Some ideas are given on the presentation and use of population forecasting results as inputs to planning. Forecasting practice and forecasting errors in The Netherlands serve as an illustration. Finally, major research topics are identified. Most prominent is the forecast of forecasting errors, in particular the separation between the impact of forecasting methodology and that of curre...

Variants of uncertainty

In contrast to formal theories of judgement and decision, which employ a single notion of probability, psychological analyses of responses to uncertainty reveal a wide variety of processes and experiences, which may follow different rules. Elementary forms of expectation and surprise in perception are reviewed. A phenomenological analysis is described, which distinguishes external attributions of uncertainty (disposition) from internal attributions of uncertainty (ignorance). Assessments of uncertainty can be made in different modes, by focusing on frequencies, propensities, the strength of arguments, or direct experiences of confidence. These variants of uncertainty are associated with different expressions in natural language; they are also suggestive of competing philosophical interpretations of probability.