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Parameter estimation in high dimensional Gaussian distributions
high dimensional Gaussian Parameter estimation massive memory
2011/6/20
In order to compute the log-likelihood for high dimensional spatial Gaussian models, it is
necessary to compute the determinant of the large, sparse, symmetric positive definite precision
matrix, Q....
Generalized Likelihood Ratio Statistics and Uncertainty Adjustments in Efficient Adaptive Design of Clinical Trials
Hoeffding’s information bound Internal pilot Kullback-Leibler information Modified Haybittle-Peto test Multiparameter exponential family Sample size re-estimation
2011/6/20
A new approach to adaptive design of clinical trials is proposed in a general multi-
parameter exponential family setting, based on generalized likelihood ratio statistics and optimal
sequential tes...
Intensity estimation of non-homogeneous Poisson processes from shifted trajectories
Poisson processes Random shifts Intensity estimation Deconvolution Meyer wavelets Adaptive estimation Besov space Minimax rate
2011/6/20
This paper considers the problem of adaptive estimation of a non-homogeneous intensity
function from the observation of n independent Poisson processes having a common intensity
that is randomly shi...
Delta method in large deviations and moderate deviations for estimators
Delta method hypothesis testing Kaplan–Meier estimator large deviations L-statistics M-estimator moderate deviations
2011/6/20
The delta method is a popular and elementary tool for deriving
limiting distributions of transformed statistics, while applications of
asymptotic distributions do not allow one to obtain desirable a...
Independent screening for single-index hazard rate models with ultra-high dimensional features
screening univariate regression models generalized linear models single-index
2011/6/17
In data sets with many more features than observations, independent screening based on all
univariate regression models leads to a computationally convenient variable selection method.
Recent effort...
A Poisson Mixed Model with Nonnormal Random Effect Distribution
Count data Generalized log-gamma distribution Multivariate negative binomial distribution Overdispersion Random-effect models
2011/6/17
We propose in this paper a random intercept Poisson model in which the random effect distribution
is assumed to follow a generalized log-gamma (GLG) distribution. We derive the first two moments
for...
Multivariate convex regression with adaptive partitioning
Nonparametric regression shape constraint convex regression treed linear model
2011/6/17
We propose a new, nonparametric method for multivariate regression subject to convexity or
concavity constraints on the response function. Convexity constraints are common in economics,
statistics, ...
Pointwise Adaptive M-estimation in Nonparametric Regression
adaptation Huber function Lepski's method M-estimation minimax estimation nonparametric regression robust estimation pointwise estimation
2011/6/17
This paper deals with the nonparametric estimation in heteroscedastic
regression Yi = f(Xi) + i; i = 1; : : : ; n, with incomplete information,
i.e. each real random variable i has a density gi wh...
CHICOM: A code of tests for comparing unweighted and weighted histograms and two weighted histograms
homogeneity test fit Monte Carlo distribution to data comparison experimental and simulated data data interpretation
2011/6/21
A self-contained Fortran-77 program for calculating test statistics to compare
weighted histogram with an unweighted histogram and two histograms with
weighted entries is presented. The code calcula...
Using Logistic Regression to Analyze the Balance of a Game: The Case of StarCraft II
Balance of a Game Logistic Regression StarCraft II
2011/6/16
Recently, the market size of online game has been increasing astonishingly fast, and so does the
importance of good game design. In online games, usually a human user competes with others,
so the fa...
Complexity of Unconstrained L_2-L_p Minimization
Nonsmooth optimization nonconvex optimization variable selection sparse solution reconstruction bridge estimator
2011/6/21
We consider the unconstrained L2-Lp minimization: find a minimizer of kAx−bk2
2+λkxkp
p
for given A ∈ Rm×n, b ∈ Rm and parameters λ > 0, p ∈ [0, 1). This problem has been
studied extensively...
A convex model for non-negative matrix factorization and dimensionality reduction on physical space
Non-negative matrix factorization dictionary learning subset selection dimensionality reduction hyperspec-tral endmember detection blind source separation
2011/3/18
A collaborative convex framework for factoring a data matrix $X$ into a non-negative product $AS$, with a sparse coefficient matrix $S$, is proposed. We restrict the columns of the dictionary matrix $...
Uncertainty quantification and weak approximation of an elliptic inverse problem
Uncertainty quantification weak approximation elliptic inverse problem
2011/3/18
We consider the inverse problem of determining the permeability from the pressure in a Darcy model of flow in a porous medium. Mathematically the problem is to find the diffusion coefficient for a lin...
Nonparametric estimation of the local Hurst function of multifractional processes
Nonparametric estimators Hurst function tangent process
2010/10/19
Consistency, almost sure convergence and central limit theorems are provided for two nonparametric estimators of the local Hurst function of Gaussian multifractional processes. In the case of multifr...
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers
unified framework high-dimensional analysis $M$-estimators decomposable regularizers
2010/10/19
High-dimensional statistical inference deals with models in which the the number of parameters $p$ is comparable to or larger than the sample size $n$. Since it is usually impossible to obtain consist...