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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
2016/1/20
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...
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...
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...
Estimating Bernoulli trial probability from a small sample
estimation of population mean sampling without replacement confidence interval coin-tossing prob-lems regularized incomplete beta function Bernoulli process
2011/6/21
The standard textbook method for estimating the probability of a biased coin from finite tosses implicitly
assumes the sample sizes are large and gives incorrect results for small samples. We describ...
Estimating the scaling function of multifractal measures and multifractal random walks using ratios
namely mutiplicative cascades structure function
2011/3/24
In this paper we prove central limit theorems for bias reduced estimators of the structure function of several multifractal processes, namely mutiplicative cascades, multifractal random measures, mult...
Estimating and forecasting partially linear models with non stationary exogeneous variables
-mixing additive models backtting electricity consumption forecasting interval semipara-metric regression smoothing
2011/3/24
This paper presents a backfitting-type method for estimating and forecasting a periodically correlated partially linear model with exogeneous variables and heteroskedastic input noise. A rate of conve...
Estimating and forecasting partially linear models with non stationary exogeneous variables
-mixing additive models backfitting electricity consumption forecasting interval semipara-metric regression smoothing
2011/3/23
This paper presents a backfitting-type method for estimating and forecasting a periodically correlated partially linear model with exogeneous variables and heteroskedastic input noise. A rate of conve...
Bounding and estimating an exceedance probability in output from monotonous computer codes
Statistics Theory (math.ST) Methodology (stat.ME)
2010/12/17
This article deals with the estimation of a probability p of an undesirable event. Its occurence is formalized by the exceedance of a threshold reliability value by the unidimensional output of a (tim...