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High-dimensional Tests for Mean Vector: Approaches without Estimating the Mean Vector Directly
Several tests for multivariate mean vector have been proposed in the recent literature. Generally, these tests are directly concerned with the mean...
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Hypothesis Testing
This chapter is one of the cornerstones of statistics because it allows us to reach a decision based on an experiment with random outcomes. The basic...
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Local Influence Detection of Conditional Mean Dependence
This article is focused on the problem to measure and test the conditional mean dependence of a response variable on a predictor variable. A local...
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Fuzzy support vector regressions for short-term load forecasting
The accurate short-term point and probabilistic load forecasts are critically important for efficient operation of power systems and electricity...
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Mean
Are brainier people . . . well, are they literally brainier? That is, do clever people have big brains? Fig. 36.1 shows a plot of IQ scores versus...
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Change Point Analysis of the Mean
We have seen that under the no change in the mean null hypothesis...
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An Extension of the Non-central Wishart Distribution with Integer Shape Vector
This research paper deals with an extension of the non-central Wishart introduced in 1944 by Anderson and Girshick, that is the non-central Riesz...
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Deep learning the efficient frontier of convex vector optimization problems
In this paper, we design a neural network architecture to approximate the weakly efficient frontier of convex vector optimization problems (CVOP)...
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Robust support vector quantile regression with truncated pinball loss (RSVQR)
Support vector quantile regression (SVQR) adapts the flexible pinball loss function for empirical risk in regression problems. Furthermore,
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The magnitude vector of images
The magnitude of a finite metric space has recently emerged as a novel invariant quantity, allowing to measure the effective size of a metric space....
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Hypothesis testing for points of impact in functional linear regression
Recently, there has been increased interest in issues related to functional linear regression models with points of impact. While the estimation of...
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Analysis of the Stock Market Crisis Based on Mean Field Games Concept
AbstractWe present an approach to describe the Chinese stock market crisis in 2015, where the shock impacts took place. Based on the Pareto demand...
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t-SNE, forceful colorings, and mean field limits
t-SNE is a commonly used force-based nonlinear dimensionality reduction method. This paper has two contributions: the first is forceful colorings , an...
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Quasi-Newton Single-Phase Stability Testing without Explicit Hessian Calculation
AbstractA robust algorithm (solver) for testing the single-phase stability of a multicomponent fluid under isochoric-isobaric conditions is...
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Testing for Error Correlation in Semi-Functional Linear Models
Existing methods for analyzing semi-functional linear models usually assumed that random errors are not serially correlated or serially correlated...
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A novel regularization-based optimization approach to sparse mean-reverting portfolios selection
The construction of profitable mean-reverting portfolios, with fewer assets, but enough volatility is a real challenge for financial investors....
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Testing Linearity in Functional Partially Linear Models
For the functional partially linear models including flexible nonparametric part and functional linear part, the estimators of the nonlinear function...
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Distributionally robust joint chance-constrained support vector machines
In this paper, we investigate the chance-constrained support vector machine (SVM) problem in which the data points are virtually uncertain although...
