Search Results - subject:"MM Algorithm"

A general inferential framework for singly-truncated bivariate normal models with applications in economics

Liu, Yin; Tian, Guo-Liang; Zhang, Chi; Qin, Hong - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015144094

Accelerated MM algorithms for inference of ranking scores from comparison data

Vojnović, Milan; Yun, Se-Young; Zhou, Kaifang - In: Operations research 71 (2023) 4, pp. 1318-1342

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014338197

Demand estimation from sales transaction data : practical extensions

Remenyi, Norbert; Luo, Xiaodong - In: Journal of revenue and pricing management 20 (2021) 3, pp. 276-300

Persistent link: https://ebvufind01.dmz1.zbw.eu/10012549332

Demand estimation under the multinomial logit model from sales transaction data

Abdallah, Tarek; Vulcano, Gustavo - In: Manufacturing & service operations management : M & SOM 23 (2021) 5, pp. 1196-1216

Persistent link: https://ebvufind01.dmz1.zbw.eu/10012653981

GenSVM: A Generalized Multiclass Support Vector Machine

Groenen, Patrick; van den Burg, G.J.J. - Faculteit der Economische Wetenschappen, Erasmus … - 2014

__Abstract__ Traditional extensions of the binary support vector machine (SVM) to multiclass problems are either heuristics or require solving a large dual optimization problem. Here, a generalized multiclass SVM called GenSVM is proposed, which can be used for classification problems where the...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011185632

Regularized (bridge) logistic regression for variable selection based on ROC criterion

Tian, GL; Fang, HB; Liu, Z; Tan, MT - 2009

minorization-maximization (MM) algorithm for non-linear optimization with positivity constraints for model fitting. This algorithm …

Persistent link: https://ebvufind01.dmz1.zbw.eu/10009471472

Quantile regression methods with varying-coefficient models for censored data

Xie, Shangyu; Wan, Alan T.K.; Zhou, Yong - In: Computational Statistics & Data Analysis 88 (2015) C, pp. 154-172

Considerable intellectual progress has been made to the development of various semiparametric varying-coefficient models over the past ten to fifteen years. An important advantage of these models is that they avoid much of the curse of dimensionality problem as the nonparametric functions are...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011264465

A new MM algorithm for constrained estimation in the proportional hazards model

Ding, Jieli; Tian, Guo-Liang; Yuen, Kam Chuen - In: Computational Statistics & Data Analysis 84 (2015) C, pp. 135-151

minorization–maximization (MM) algorithm is developed for calculating the maximum likelihood estimates of the regression … MM algorithm is to construct a surrogate function with a diagonal Hessian matrix, which can be reached by utilizing the …. The ascent property of the proposed MM algorithm under constraints is theoretically justified. Standard error estimation …

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011191012

Estimating common principal components in high dimensions

Browne, Ryan; McNicholas, Paul - In: Advances in Data Analysis and Classification 8 (2014) 2, pp. 217-226

We consider the problem of minimizing an objective function that depends on an orthonormal matrix. This situation is encountered, for example, when looking for common principal components. The Flury method is a popular approach but is not effective for higher dimensional problems. We obtain...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010846120

A coordinate descent MM algorithm for fast computation of sparse logistic PCA

Lee, Seokho; Huang, Jianhua Z. - In: Computational Statistics & Data Analysis 62 (2013) C, pp. 26-38

Sparse logistic principal component analysis was proposed in Lee et al. (2010) for exploratory analysis of binary data. Relying on the joint estimation of multiple principal components, the algorithm therein is computationally too demanding to be useful when the data dimension is high. We...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011056490