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Estimating Spatial Autocorrelation with Sampled Network Data
NetworkDataAnalysis Paired Maximum Likelihood Estimator
2016/1/26
Spatial autocorrelation is a parameter of importance for network data analysis. To estimate spatial autocorrelation, maximum likelihood has been popularly used. However, its rigorous implementation re...
Estimating Mixture of Gaussian Processes by Kernel Smoothing
Identifiability EM algorithm Kernel regression Gaussian process Functional principal component analysis
2016/1/26
When the functional data are not homogeneous, e.g., there exist multiple classes of func-tional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimati...
Estimating Mixture of Gaussian Processes by Kernel Smoothing
Identifiability EM algorithm Kernel regression Gaussian process Functional principal component analysis
2016/1/20
When the functional data are not homogeneous, e.g., there exist multiple classes of func-tional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimati...
Estimating Tail Probabilities in Queues via Extremal Statistics
Extreme values queues regenerative processes rare events estimation asymptotics
2015/7/8
We study the estimation of tail probabilities in a queue via a semi-parametric estimator based on the maximum value of the workload, observed over the sampled time interval. Logarithmic consistency an...
Estimating Average Causal Effects Under Interference Between Units
Estimating Average Causal Effects Interference Between Units
2013/6/14
This paper presents a randomization-based framework for estimating causal effects under interference between units. We develop the case of estimating average unit-level causal effects from a randomize...
Estimating treatment effect heterogeneity in randomized program evaluation
Causal inference individualized treatment rules LASSO moderation variable selection
2013/6/14
When evaluating the efficacy of social programs and medical treatments using randomized experiments, the estimated overall average causal effect alone is often of limited value and the researchers mus...
A Bayesian localised conditional auto-regressive model for estimating the health effects of air pollution
Air pollution and health Conditional autoregressive models Spatial correlation
2013/6/14
Estimation of the long-term health effects of air pollution is a challenging task, especially when modelling small-area disease incidence data in an ecological study design. The challenge comes from t...
Estimating Network Degree Distributions Under Sampling: An Inverse Problem, with Applications to Monitoring Social Media Networks
Estimating Network Degree Distributions Sampling An Inverse Problem Applications Monitoring Social Media Networks
2013/6/14
Networks are a popular tool for representing elements in a system and their interconnectedness. Many observed networks can be viewed as only samples of some true underlying network. Such is frequently...
Estimating the quadratic covariation of an asynchronously observed semimartingale with jumps
asynchronous observations co-jumps statistics of semimartingales quadratic covariation
2013/6/14
We consider estimation of the quadratic (co)variation of a semimartingale from discrete observations which are irregularly spaced under high-frequency asymptotics. In the univariate setting, results b...
A General Family of Estimators for Estimating Population Mean in Systematic Sampling Using Auxiliary Information in the Presence of Missing Observations
Family of estimators Auxiliary information Mean square error Non-response Systematic sampling
2013/6/14
This paper proposes a general family of estimators for estimating the population mean in systematic sampling in the presence of non-response adapting the family of estimators proposed by Khoshnevisan ...
Estimating the quadratic covariation matrix from noisy observations: local method of moments and efficiency
adaptive estimation asymptotic equivalence asynchronous ob-servations integrated covolatility matrix quadratic covariation semiparametric eciency,microstructure noise spectral estimation
2013/4/28
An efficient estimator is constructed for the quadratic covariation or integrated covolatility matrix of a multivariate continuous martingale based on noisy and non-synchronous observations under high...
TIGER: A Tuning-Insensitive Approach for Optimally Estimating Gaussian Graphical Models
TIGER Tuning-Insensitive Approach Optimally Estimating Gaussian Graphical Models
2012/11/22
We propose a new procedure for estimating high dimensional Gaussian graphical models. Our approach is asymptotically tuning-free and non-asymptotically tuning-insensitive: it requires very few efforts...
Estimating a Causal Order among Groups of Variables in Linear Models
Causal Order among Groups Variables in Linear Models
2012/9/19
The machine learning community has recently devoted much attention to the problem of inferring causal relationships from statistical data. Most of this work has focused on uncovering connections among...
Estimating Failure Probabilities
asymptotic normality exceedance probability failure set homogeneity
2011/7/19
In risk management often the probability must be estimated that a random vector falls into an extreme failure set. In the framework of bivariate extreme value theory, we construct an estimator for suc...
A two-stage hybrid procedure for estimating an inverse regression function
Two-stage estimator bootstrap adaptive design asymptotic properties
2011/6/17
We consider a two-stage procedure (TSP) for estimating an inverse
regression function at a given point, where isotonic regression
is used at stage one to obtain an initial estimate and a local linea...