Results 31 to 40 of about 76,132 (306)
The Measurement Invariance of Schizotypy in Europe [PDF]
European Psychiatry, 2015 AbstractThe short version of the Oxford-Liverpool Inventory of Feelings and Experiences (sO-LIFE) is a widely used measure assessing schizotypy. There is limited information, however, on how sO-LIFE scores compare across different countries. The main goal of the present study is to test the measurement invariance of the sO-LIFE scores in a large sample
Fonseca-Pedrero E +7 more
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Dynamics of Systems with a Discontinuous Hysteresis Operator and Interval Translation Maps
Axioms, 2021 We studied topological and metric properties of the so-called interval translation maps (ITMs). For these maps, we introduced the maximal invariant measure and study its properties. Further, we study how the invariant measures depend on the parameters of
Sergey Kryzhevich +4 more
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The Annals of Probability, 1973 Let $\mu$ be a probability measure on $(\mathscr{R}, \mathscr{B})$, where $\mathscr{R}$ is the real line and $\mathscr{B}$ the family of Borel sets on $\mathscr{R}$. A measurable set `$A$' is called $\mu$-invariant if $\mu(A + \theta) = \mu(A) \mathbf{\forall} \theta, -\infty < \theta < \infty$.
Blum, Julius R., Pathak, Pramod K.
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Moment estimates for invariant measures of stochastic Burgers equations
Advances in Difference Equations, 2020 In this paper, we study moment estimates for the invariant measure of the stochastic Burgers equation with multiplicative noise. Based upon an a priori estimate for the stochastic convolution, we derive regularity properties on invariant measure.
Yu Shi, Bin Liu
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Deep Equal Risk Pricing of Financial Derivatives with Non-Translation Invariant Risk Measures
Risks, 2023 The objective is to study the use of non-translation invariant risk measures within the equal risk pricing (ERP) methodology for the valuation of financial derivatives.
Alexandre Carbonneau, Frédéric Godin
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Measurement Invariance, Entropy, and Probability [PDF]
Entropy, 2010 We show that the natural scaling of measurement for a particular problem defines the most likely probability distribution of observations taken from that measurement scale. Our approach extends the method of maximum entropy to use measurement scale as a type of information constraint.
Steven A. Frank, D. Eric Smith
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Law invariant risk measures and information divergences
Dependence Modeling, 2018 Aone-to-one correspondence is drawnbetween lawinvariant risk measures and divergences,which we define as functionals of pairs of probability measures on arbitrary standard Borel spaces satisfying a few natural properties.
Lacker Daniel
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background PIK3CA‐related overgrowth spectrum (PROS) includes several rare overgrowth disorders resulting from somatic gain‐of‐function mutations in PIK3CA. Despite treatment advances, including the recent approval of alpelisib for PROS in the United States, literature detailing the patient experience with PROS is limited.
Vamsi Bollu +8 more
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Bayesian invariant measurements of generalization [PDF]
Neural Processing Letters, 1995 The problem of evaluating different learning rules and other statistical estimators is analysed. A new general theory of statistical inference is developed by combining Bayesian decision theory with information geometry. It is coherent and invariant. For each sample a unique ideal estimate exists and is given by an average over the posterior.
Huaiyu Zhu 0001, Richard Rohwer
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Sublinear functionals ergodicity and finite invariant measures
International Journal of Mathematics and Mathematical Sciences, 1989 By introducing a sublinear functional involving infinite matrices, we establish its connection with ergodicity and measure preserving transformation. Further, we characterize the existence of a finite invariant measure by means of a condition involving ...
G. Das, B. K. Patel
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