Search results for " Uncertainty"

Multiplicity- and dependency-adjusted p-values for control of the family-wise error rate

2016

Abstract Under the multiple testing framework, we propose the multiplicity- and dependency-adjustment method (MADAM) which transforms test statistics into adjusted p -values for control of the family-wise error rate. For demonstration, we apply the MADAM to data from a genetic association study.

bookdown: Authoring Books and Technical Documents with R Markdown

2018

Pitfalls of hypothesis tests and model selection on bootstrap samples: Causes and consequences in biometrical applications

2015

The bootstrap method has become a widely used tool applied in diverse areas where results based on asymptotic theory are scarce. It can be applied, for example, for assessing the variance of a statistic, a quantile of interest or for significance testing by resampling from the null hypothesis. Recently, some approaches have been proposed in the biometrical field where hypothesis testing or model selection is performed on a bootstrap sample as if it were the original sample. P-values computed from bootstrap samples have been used, for example, in the statistics and bioinformatics literature for ranking genes with respect to their differential expression, for estimating the variability of p-v…

Heritability of Lifetime Income

2013

Using 15 years of data on Finnish twins, we find that 24% (54%) of the variance of women’s (men’s) lifetime income is due to genetic factors and that the contribution of the shared environment is negligible. We link these figures to policy by showing that controlling for education reduces the variance share of genetics by 5-8 percentage points; by demonstrating that income uncertainty has a genetic component half the size of its variance share in lifetime income; and by exploring how the genetic heritability of lifetime income is related to the macroeconomic environment, as measured by GDP growth and the Gini-coefficient of income inequality.

Financial contagion through space-time point processes

2020

AbstractWe propose to study the dynamics of financial contagion by means of a class of point process models employed in the modeling of seismic contagion. The proposal extends network models, recently introduced to model financial contagion, in a space-time point process perspective. The extension helps to improve the assessment of credit risk of an institution, taking into account contagion spillover effects.

Dysfunctional beliefs about health and illness: a family study

2019

espanolLos modelos cognitivos sobre la hipocondria postulan que las experiencias tempranas con la enfermedad promueven el desarrollo de creencias disfuncionales sobre la enfermedad. Estas creencias pueden permanecer latentes y activarse ante un incidente critico. Los estudios publicados aportan datos que avalan de manera indirecta estos planteamientos. Teniendo en cuenta que en el nucleo familiar primario se comparten experiencias sobre la enfermedad, examinamos la relacion entre las creencias disfuncionales que los progenitores y sus descendientes mantienen sobre la enfermedad y los pensamientos, tales como la intolerancia a la incertidumbre y la sobreestimacion de la amenaza, y las relaci…

Inattention and Uncertainty in the Predictive Brain

2021

Negative effects of inattention on task performance can be seen in many contexts of society and human behavior, such as traffic, work, and sports. In traffic, inattention is one of the most frequently cited causal factors in accidents. In order to identify inattention and mitigate its negative effects, there is a need for quantifying attentional demands of dynamic tasks, with a credible basis in cognitive modeling and neuroscience. Recent developments in cognitive science have led to theories of cognition suggesting that brains are an advanced prediction engine. The function of this prediction engine is to support perception and action by continuously matching incoming sensory input with to…

On the stability of some controlled Markov chains and its applications to stochastic approximation with Markovian dynamic

2015

We develop a practical approach to establish the stability, that is, the recurrence in a given set, of a large class of controlled Markov chains. These processes arise in various areas of applied science and encompass important numerical methods. We show in particular how individual Lyapunov functions and associated drift conditions for the parametrized family of Markov transition probabilities and the parameter update can be combined to form Lyapunov functions for the joint process, leading to the proof of the desired stability property. Of particular interest is the fact that the approach applies even in situations where the two components of the process present a time-scale separation, w…

Coupled conditional backward sampling particle filter

2020

The conditional particle filter (CPF) is a promising algorithm for general hidden Markov model smoothing. Empirical evidence suggests that the variant of CPF with backward sampling (CBPF) performs well even with long time series. Previous theoretical results have not been able to demonstrate the improvement brought by backward sampling, whereas we provide rates showing that CBPF can remain effective with a fixed number of particles independent of the time horizon. Our result is based on analysis of a new coupling of two CBPFs, the coupled conditional backward sampling particle filter (CCBPF). We show that CCBPF has good stability properties in the sense that with fixed number of particles, …

From Feynman–Kac formulae to numerical stochastic homogenization in electrical impedance tomography

2016

In this paper, we use the theory of symmetric Dirichlet forms to derive Feynman–Kac formulae for the forward problem of electrical impedance tomography with possibly anisotropic, merely measurable conductivities corresponding to different electrode models on bounded Lipschitz domains. Subsequently, we employ these Feynman–Kac formulae to rigorously justify stochastic homogenization in the case of a stochastic boundary value problem arising from an inverse anomaly detection problem. Motivated by this theoretical result, we prove an estimate for the speed of convergence of the projected mean-square displacement of the underlying process which may serve as the theoretical foundation for the de…