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A Random Matrix--Theoretic Approach to Handling Singular Covariance Estimates
Random Matrix--Theoretic Approach Handling Singular Covariance Estimates
2010/10/19
In many practical situations we would like to estimate the covariance matrix of a set of variables from an insufficient amount of data. More specifically, if we have a set of $N$ independent, identica...
Some Theory for the Analysis of Random Fields——With Applications to Geostatistics
Some Theory Random Fields Applications to Geostatistics
2010/4/26
Ich erkl¨are ehrenw¨ortlich, dass ich die vorliegende Schrift verfasst und die
mit ihr unmittelbar verbundenen Arbeiten selbst durchgef¨uhrt habe. Die in
der Schrift verwendete Literatur sowie das A...
Beta-binomial/gamma-Poisson regression models for repeated counts with random parameters
bivariate counts longitudinal data overdispersion random effects regressionmodels
2010/3/11
Beta-binomial/Poisson models have been used by many authors to model multivariate
count data. Lora and Singer (Statistics in Medicine, 2008) extended such models
to accommodate repeated multivariate...
Defining probability density for a distribution of random functions
Density estimation dimension eigenfunction eigenvalue functionaldata analysis kernel methods log-density estimation nonparametric statistics
2010/3/11
The notion of probability density for a random function is not
as straightforward as in finite-dimensional cases. While a probability
density function generally does not exist for functional data, w...
On the neighborhood radius estimation in Variable-neighborhood Markov Random Fields
Gibbs measures random lattice fields variable-neighborhood Markovrandom fields Markovian approximations Context algorithm consistent estimation
2010/3/11
We consider Markov Random Fields defined by finite-region conditional probabilities
depending on a neighborhood of the region which changes with the boundary conditions.
The formal definition of the...
Estimation in Dirichlet random effects models
Linear mixed models generalized linear mixed models hierarchicalmodels Gibbs sampling Bayes estimation
2010/3/10
We also investigate methods for the estimation of the precision parameter
of the Dirichlet process, finding that maximum likelihood
may not be desirable, but a posterior mode is a reasonable approac...
On the posterior distribution of classes of random means
Bayesian nonparametrics completely random measures means of randomprobability measures normalized random measures Poisson–Dirichlet process
2010/3/10
The study of properties of mean functionals of random probability measures is an important
area of research in the theory of Bayesian nonparametric statistics. Many results are now known
for random ...
The shortest distance in random multi-type intersection graphs
Intersection graph shortest path branching process approximation Poissonapproximation
2010/3/9
Using an associated branching process as the basis of our approximation, we
show that typical inter-point distances in a multitype random intersection graph
have a defective distribution, which is w...
On a random number of disorders
disorder problem sequential detection optimalstopping Markov process change point double optimal stopping
2010/3/17
We register a random sequence which has the following
properties: it has three segments being the homogeneous Markov processes.
Each segment has his own one step transition probability law and the l...
Exact lower bounds on the exponential moments of Winsorized and truncated random variables
exponential moments exact lower bounds Win-sorization truncation large deviations nonuniform Berry-Esseen bounds
2010/3/9
Exact lower bounds on the exponential moments of min(y,X)
and X I {X < y} are provided given the first two moments of a random
variable X. These bounds are useful in work on large deviations probabi...
On the approximation of mean densities of random closed sets
mean densities random measures stochastic geometry
2010/3/9
Many real phenomena may be modelled as random closed sets in Rd, of different Hausdorff dimensions.
In many real applications, such as fiber processes and n-facets of random tessellations
of dimensi...
Random walks-a sequential approach
Control chart nonparametric smoothing sequential analysis unit roots weighted partial sum process
2010/3/9
In this paper sequential monitoring schemes to detect nonparametric drifts
are studied for the random walk case. The procedure is based on a kernel smoother. As
a by-product we obtain the asymptotic...
A functional limit theorem for partial sums of dependent random variables with infinite variance
convergence in distribution functional limit the-orem GARCH mixing moving average partial sum point processes reg-ular variation
2010/3/9
Under an appropriate regular variation condition, the affinely
normalized partial sums of a sequence of independent and identically dis-
tributed random variables converges weakly to a non-Gaussian ...
The spectrum of kernel random matrices
spectrum kernel random matrices high-dimensional statisticalinference
2010/3/9
We place ourselves in the setting of high-dimensional statistical
inference where the number of variables p in a dataset of interest is
of the same order of magnitude as the number of observations n...
Coherence-Based Performance Guarantees for Estimating a Sparse Vector Under Random Noise
Coherence-Based Performance Guarantees Sparse Vector Random Noise
2010/3/19
We consider the problem of estimating a deterministic
sparse vector x0 from underdetermined measurements
Ax0 + w, where w represents white Gaussian noise and A is
a given deterministic dictionary. ...