SelectedWorks - Leming Qu

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Selected Works of Leming Qu

Department Chair and Associate Professor, Department of Mathematics

Dr. Leming Qu joined the faculty of the Department of Mathematics at Boise State University in 2002. He earned a B.S. in Mathematics and an M.A. in Economics from Nanjing University, and then went on to earn an M.S. in Applied Statistics and his Ph.D. in Statistics, both from Purdue University. Dr. Qu's research interests include computational statistics, statistical and computational inverse problems, statistical learning, and statistical signal and image processing.

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About Leming Qu

Dr. Leming Qu joined the faculty of the Department of Mathematics at Boise State University in 2002. He earned a B.S. in Mathematics and an M.A. in Economics from Nanjing University, and then went on to earn an M.S. in Applied Statistics and his Ph.D. in Statistics, both from Purdue University. Dr. Qu's research interests include computational statistics, statistical and computational inverse problems, statistical learning, and statistical signal and image processing.

Present	Department Chair and Associate Professor, Department of Mathematics, Boise State University ‐ Department of Mathematics
Institution Organization Position Type Position Title Time Period to Options Current Position Affiliate my profile with this Institution

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Statistics and Computational Statistics

MATH 574: Linear Models
MATH 572: Computational Statistics
MATH 471: Data Analysis-- Elements of Statistical Computing
MATH 462/562: Probability and Statistics ΙI
MATH 361: Probability and Statistics Ι
MATH 360: Engineering Statistics
MATH 254: Applied Statistics with Computers
MATH 170: Calculus I

E-mail: lqu@boisestate.edu

http://orcid.org/0000-0001-9890-2704

Articles & Conference Proceedings (17)

Copula Density Estimation by Finite Mixture of Parametric Copula Densities (Leming Qu and Yang Lu) Communications in Statistics: Simulation and Computation (2021)

A copula density estimation method that is based on a finite mixture of heterogeneous parametric copula densities is proposed here. More specifically, the mixture components are Clayton, Frank, Gumbel, T, and normal copula densities, which ...

Copula Density Estimation by Total Variation Penalized Likelihood with Linear Equality Constraints (Leming Qu and Wotao Yin) Computational Statistics & Data Analysis (2012)

A copula density is the joint probability density function (PDF) of a random vector with uniform marginals. An approach to bivariate copula density estimation is introduced that is based on a maximum penalized likelihood estimation ...

Nonparametric Copula Density Estimation in Sensor Networks (Leming Qu, Hao Chen and Yicheng Tu) Seventh International Conference on Mobile Ad-hoc and Sensor Networks (MSN) (2011)

Statistical and machine learning is a fundamental task in sensor networks. Real world data almost always exhibit dependence among different features. Copulas are full measures of statistical dependence among random variables. Estimating the underlying copula ...

A Semiparametric Approach for Analyzing Nonignorable Missing Data (Hui Xie, Yi Qian and Leming Qu) Statistica Sinica (2011)

In missing data analysis, there is often a need to assess the sensitivity of key inferences to departures from untestable assumptions regarding the missing data process. Such sensitivity analysis often requires specifying a missing data ...

Wavelet Image Restoration and Regularization Parameters Selection (Leming Qu) Fourth International Conference on Frontier of Computer Science and Technology, 2009. FCST '09 (2010)

For the restoration of an image based on its noisy distorted observations, we propose wavelet domain restoration by scale-dependent ∫1 penalized regularization method (WaveRSL1). The data adaptive choice of the regularization parameters is based on ...

Rayleigh Wave Dispersion Curve Inversion: Occam Versus the L1-Norm (Matthew M. Haney and Leming Qu) SEG Expanded Abstracts (2010)

We compare inversions of Rayleigh wave dispersion curves for shear wave velocity depth profiles based on the L2-norm (Occam's Inversion) and L1-norm (TV Regularization). We forward model Rayleigh waves using a finite-element method instead of ...

Copula Density Estimation by Total Variation Penalized Likelihood (Leming Qu, Yi Qian and Hui Xie) Communications in Statistics - Simulation and Computation (2009)

Copulas are full measures of dependence among random variables. They are increasingly popular among academics and practitioners in financial econometrics for modeling comovements between markets, risk factors, and other relevant variables. A copula's hidden dependence ...

Wavelet-Based Bayesian Estimation of Partially Linear Regression Models with Long Memory Errors (Kyungduk Ko, Leming Qu and Marina Vannucci) Statistica Sinica (2009)

In this paper we focus on partially linear regression models with long memory errors, and propose a wavelet-based Bayesian procedure that allows the simultaneous estimation of the model parameters and the nonparametric part of the ...

Copula Density Estimation by Total Variation Penalized Likelihood (Leming Qu, Yi Qian and Hui Xie) Communications in Statistics: Simulation and Computation (2009)

Copulas are full measures of dependence among random variables. They are increasingly popular among academics and practitioners in financial econometrics for modeling comovements between markets, risk factors, and other relevant variables. A copula's hidden dependence ...

Wavelet Reconstruction of Nonuniformly Sampled Signals (Leming Qu, Partha S. Routh and Phil D. Anno) IEEE Signal Processing Letters (2009)

For the reconstruction of a nonuniformly sampled signal based on its noisy observations, we propose a level dependent l1 penalized wavelet reconstruction method. The LARS/Lasso algorithm is applied to solve the Lasso problem. The data ...

Inversion for Non-Smooth Models with Physical Bounds (Partha S. Routh, Leming Qu, Mrinal K. Sen, et al.) SEG Expanded Abstracts (2007)

Geological processes produce structures at multiple scales. A discontinuity in the subsurface can occur due to layering, tectonic activities such as faulting, folding and fractures. Traditional approaches to invert geophysical data employ smoothness constraints. Such ...

Change Point Estimation of Bilevel Functions (Leming Qu and Yi-Cheng Tu) Journal of Modern Applied Statistical Methods (2006)

Reconstruction of a bilevel function such as a bar code signal in a partially blind deconvolution problem is an important task in industrial processes. Existing methods are based on either the local approach or the ...

Bayesian Wavelet Estimation of Partially Linear Models (Leming Qu) Journal of Statistical Computation and Simulation (2006)

A Bayesian wavelet approach is presented for estimating a partially linear model (PLM). A PLM consists of a linear part and a nonparametric component. The nonparametric component is represented with a wavelet series where the ...

Wavelet Deconvolution in a Periodic Setting Using Cross-Validation (Leming Qu, Partha S. Routh and Kyungduk Ko) IEEE Signal Processing Letters (2006)

The wavelet deconvolution method WaveD using band-limited wavelets offers both theoretical and computational advantages over traditional compactly supported wavelets. The translation-invariant WaveD with a fast algorithm improves further. The twofold cross-validation method for choosing the ...

Bayesian Wavelet Estimation of Long Memory Parameter (Leming Qu) Journal of Modern Applied Statistical Methods (2005)

A Bayesian wavelet estimation method for estimating parameters of a stationary I(d) process is represented as an useful alternative to the existing frequentist wavelet estimation methods. The effectiveness of the proposed method is demonstrated through ...

Wavelet Estimation of Partially Linear Models (Xiao-Wen Chang and Leming Qu) Computational Statistics & Data Analysis (2004)

A wavelet approach is presented for estimating a partially linear model (PLM). We find an estimator of the PLM by minimizing the square of the l2 norm of the residual vector while penalizing the l1 ...

Wavelet Thresholding in Partially Linear Models: A Computation and Simulation (Leming Qu) Applied Stochastic Models in Business and Industry (2003)

Partially linear models have a linear part as in the linear regression and a non-linear part similar to that in the non-parametric regression. The estimates in Partially Linear Models have been studied previously using traditional ...

On semiparametric regression via wavelets (Leming Qu) Theses and Dissertations Available from ProQuest (2002)

Semiparametric regression models have a linear part as in the linear regression and a nonlinear part similar to that in the nonparametric regression. The estimates in semiparametric regression models have been studied previously in traditional ...