Results 41 to 50 of about 442,883 (292)

Nonparametric Testing for Information Asymmetry in the Mortgage Servicing Market

Risks
Our objective is to test for evidence of information asymmetry in the mortgage servicing market. Does the sale of mortgage servicing rights (MSR) by the initial lender to a second servicing institution unveil any residual asymmetric information?
Helmi Jedidi, Georges Dionne
doaj   +1 more source

Nonparametric Functional Data Analysis for Forecasting Container Throughput: The Case of Shanghai Port

Journal of Marine Science and Engineering, 2022
Transportation is one of the major carbon sources in China. Container throughput is one of the main influencing factors of ports’ carbon emission budget, and accurate prediction of container throughput is of great significance to the study of carbon ...
Yuye Zou, Bohan Su, Yanhui Chen
doaj   +1 more source

Monitoring of circulating tumor DNA allows early detection of disease relapse in patients with operable breast cancer

Molecular Oncology, EarlyView.
Monitoring circulating tumor DNA (ctDNA) in patients with operable breast cancer can reveal disease relapse earlier than radiology in a subset of patients. The failure to detect ctDNA in some patients with recurrent disease suggests that ctDNA could serve as a supplement to other monitoring approaches.
Kristin Løge Aanestad, Marie Austdal, Oddmund Nordgård, Gunnar Mellgren, Satu Oltedal, Marie L. Austbø, Ylva H. Vignes, Thomas Helland, Kristin Jonsdottir, Tone H. Lende, Emilius A. M. Janssen, Bjørnar Gilje, Kjersti Tjensvoll, PBCB study group, Gunnar Mellgren, Tone Hoel Lende, Anette Heie, Kristin Viste, Anita Røyneberg Alvheim, Emiel AM Janssen, Kristin Jonsdottir, Ann Cathrine Kroksveen, Thomas Helland, Einar Gudlaugsson, Oddmund Nordgård, Satu Oltedal, Kristin Løge Aanestad, Jan Terje Kvaløy, Kirsten Lode, Kari Britt Hagen, Marie Austdal, Ylva H. Vignes, Siri Tungland Sola, Nina Egeland Amundsen, Finn Magnus Eliassen, Emeritus Ernst A Lien   +35 more
wiley   +1 more source

Weighted Kernel Ridge Regression to Improve Genomic Prediction

Agriculture
Nonparametric models have recently been receiving increased attention due to their effectiveness in genomic prediction for complex traits. However, regular nonparametric models cannot effectively differentiate the relative importance of various SNPs ...
Chenguang Diao, Yue Zhuo, Ruihan Mao, Weining Li, Heng Du, Lei Zhou, Jianfeng Liu   +6 more
doaj   +1 more source

Conjugate Projective Limits [PDF]

, 2011
We characterize conjugate nonparametric Bayesian models as projective limits of conjugate, finite-dimensional Bayesian models. In particular, we identify a large class of nonparametric models representable as infinite-dimensional analogues of exponential
Orbanz, Peter
core  

Nonparametric Independence Screening in Sparse Ultra-High Dimensional Varying Coefficient Models

, 2013
The varying-coefficient model is an important nonparametric statistical model that allows us to examine how the effects of covariates vary with exposure variables. When the number of covariates is big, the issue of variable selection arrives.
Dai, Wei, Fan, Jianqing, Ma, Yunbei
core   +1 more source

LINC01116, a hypoxia‐lncRNA marker of pathological lymphangiogenesis and poor prognosis in lung adenocarcinoma

Molecular Oncology, EarlyView.
The LINC01116 long noncoding RNA is induced by hypoxia and associated with poor prognosis and high recurrence rates in two cohorts of lung adenocarcinoma patients. Here, we demonstrate that besides its expression in cancer cells, LINC01116 is markedly expressed in lymphatic endothelial cells of the tumor stroma in which it participates in hypoxia ...
Marine Gautier‐Isola, Rafael Lopes Goncalves, Marin Truchi, Caroline Lacoux, Célia Scribe, Hugo Cadis, Laetitia Guardini, Sophie Bekisz, Marius Ilié, Paul Hofman, Georges Vassaux, Bernard Mari, Roger Rezzonico   +12 more
wiley   +1 more source

Sparse Additive Models

, 2008
We present a new class of methods for high-dimensional nonparametric regression and classification called sparse additive models (SpAM). Our methods combine ideas from sparse linear modeling and additive nonparametric regression.
Lafferty, John, Liu, Han, Ravikumar, Pradeep, Wasserman, Larry   +3 more
core   +2 more sources

Semiparametric Bayesian inference in multiple equation models [PDF]

, 2005
This paper outlines an approach to Bayesian semiparametric regression in multiple equation models which can be used to carry out inference in seemingly unrelated regressions or simultaneous equations models with nonparametric components.
Koop, Gary, Poirier, Dale J., Tobias, Justin   +2 more
core   +1 more source

Nonparametric longitudinal allele-sharing model [PDF]

BMC Genetics, 2003
AbstractBasically no methods are available for the analysis of quantitative traits in longitudinal genetic epidemiological studies. We introduce a nonparametric factorial design for longitudinal data on independent sib pairs, modelling the phenotypic quadratic differences as the dependent variable.
Kulle, Bettina, Kohler, K., Rosenberger, Albert, Loesgen, S., Bickeboeller, Heike   +4 more
openaire   +3 more sources