We provide an approach for learning deep neural net representations of models described via conditional moment restrictions. Conditional moment restrictions are widely used, as they are the language by which social scientists describe the assumptions they make to enable causal inference. We formulate the problem of estimating the underling model as a zero-sum game between a modeler and an adver...

Shanker [4] has discussed its various mathematical and statistical properties including its shape for different values of its parameter, moment generating function, moments, skewness, kurtosis, hazard rate function, mean residual life function, stochastic orderings, mean deviations, Bonferroni and Lorenz curves, amongst others. Further, Shanker [4] has also discussed the estimation of its param...

in this parer the iteration method (kani's method) is developed for the analysis of arch - frames. the method takes the effect of linear displacements of joints automatically into account. therefore, it is more efficient than moment distribution method. the iteration procedure can be applied to any kind of framed structure. a hand calculator or a computer may be used in the analysis of fra...

Auto-regulation, a process wherein a protein negatively regulates its own production, is a common motif in gene expression networks. Negative feedback in gene expression plays a critical role in buffering intracellular fluctuations in protein concentrations around optimal value. Due to the nonlinearities present in these feedbacks, moment dynamics are typically not closed, in the sense that the...

Mixture modeling is a general technique for making any simple model more expressive through weighted combination. This generality and simplicity in part explains the success of the Expectation Maximization (EM) algorithm, in which updates are easy to derive for a wide class of mixture models. However, the likelihood of a mixture model is non-convex, so EM has no known global convergence guarant...

In this paper the Quality measures of Multispectral images are analysed by using Textual features. An experimental result of textual features on different tasks in multispectral images vise TM, SAR is measured. Six different statistical moments based on common descriptors of the features are measured and based on those statistical moments, Quality measures are analyzed.

Abstract. We present a pixel-level fusion method to refine the resolution of a multi-spectral image using a high-resolution panchromatic image. Our approach is an adaptation of the ARSIS method which takes into account the higher-order statistical moments of the wavelet coefficients. The use of the stationary wavelet transform allows the fusion between images of non-dyadic dimension with less “...

The increasing interest in processing sequences of images motivates development of techniques for sequence-based object analysis and description. Accordingly, new velocity moments have been developed to allow a statistical description of both shape and associated motion through an image sequence. Through a generic framework motion information is determined using the established centralised mome...

Solving the Saint-Venant equations by numerical methods like finite element and finite difference methods yields an unstable solution for a fairly large open channel. Multiple Knot B-Spline Wavelets (MKBSW) are in the class of semi-orthogonal wavelets that have compact support. Hence, these basis functions are suitable for solving the Saint-Venant equations. However, solving the Saint-Venant eq...