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Composite likelihood methods for parsimonious model-based clustering of mixed-type data
In this paper, we propose twelve parsimonious models for clustering mixed-type (ordinal and continuous) data. The dependence among the different...
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Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data
Topic models are a useful and popular method to find latent topics of documents. However, the short and sparse texts in social media micro-blogs such...
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Weighted high dimensional data reduction of finite element features: an application on high pressure of an abdominal aortic aneurysm
In this work we propose a low rank approximation of areal, particularly three dimensional, data utilizing additional weights. This way we enable...
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GOLFS: feature selection via combining both global and local information for high dimensional clustering
It is important to identify the discriminative features for high dimensional clustering. However, due to the lack of cluster labels, the...
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Imputation-based empirical likelihood inferences for partially nonlinear quantile regression models with missing responses
In this paper, we consider the confidence interval construction for the partially nonlinear models with missing responses at random under the...
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Fisher Scoring for crossed factor linear mixed models
The analysis of longitudinal, heterogeneous or unbalanced clustered data is of primary importance to a wide range of applications. The linear mixed...
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Partial least square based approaches for high-dimensional linear mixed models
To deal with repeated data or longitudinal data, linear mixed effects models are commonly used. A classical parameter estimation method is the...
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Optimal Liquidation Through a Limit Order Book: A Neural Network and Simulation Approach
We present a learning algorithm based on simulation and neural networks to solve a stochastic optimal control problem with a large state space using...
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Pseudo-value regression trees
This paper presents a semi-parametric modeling technique for estimating the survival function from a set of right-censored time-to-event data. Our...
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Goodness of fit test for Rayleigh distribution with censored observations
We develop new goodness of fit tests for Rayleigh distribution based on fixed point characterization. We use U-Statistic theory to derive the test...
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Zero-Inflated Time Series Clustering Via Ensemble Thick-Pen Transform
This study develops a new clustering method for high-dimensional zero-inflated time series data. The proposed method is based on thick-pen transform...
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Variational inference for semiparametric Bayesian novelty detection in large datasets
After being trained on a fully-labeled training set, where the observations are grouped into a certain number of known classes, novelty detection...
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Semiparametric likelihood inference for heterogeneous survival data under double truncation based on a Poisson birth process
We study a selective sampling scheme in which survival data are observed during a data collection period if and only if a specific failure event is...
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Lean Six Sigma and TPM for the Improvement of Equipment Maintenance Process in a Service Sector Company: A Case Study
Currently, competitiveness within the service industry has reached outstanding levels. In the pursuit of increasing the quality and efficiency of...
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Simulation Methods for the Analysis of Complex Systems
Everyday systems like communication, transportation, energy and industrial systems are an indispensable part of our daily lives. Several methods have...
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Communication-efficient distributed estimation for high-dimensional large-scale linear regression
In the Master-Worker distributed structure, this paper provides a regularized gradient-enhanced loss (GEL) function based on the high-dimensional...
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Robust variable selection with exponential squared loss for partially linear spatial autoregressive models
In this paper, we consider variable selection for a class of semiparametric spatial autoregressive models based on exponential squared loss (ESL)....
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Use of the heuristic optimization in the parameter estimation of generalized gamma distribution: comparison of GA, DE, PSO and SA methods
The generalized gamma distribution (GGD) is a popular distribution because it is extremely flexible. Due to the density function structure of GGD,...
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A two-stage Bridge estimator for regression models with endogeneity based on control function method
In this study, we investigate a penalty-based two-stage least square estimator in regression models when the exploratory variables are correlated...
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Robust beta regression through the logit transformation
Beta regression models are employed to model continuous response variables in the unit interval, like rates, percentages, or proportions. Their...
