Results 71 to 80 of about 1,722,167 (288)

Estimation of the density of regression errors

, 2006
Estimation of the density of regression errors is a fundamental issue in regression analysis and it is typically explored via a parametric approach. This article uses a nonparametric approach with the mean integrated squared error (MISE) criterion.
Efromovich, Sam
core   +1 more source

Contingent Kernel Density Estimation

PLoS ONE, 2012
Kernel density estimation is a widely used method for estimating a distribution based on a sample of points drawn from that distribution. Generally, in practice some form of error contaminates the sample of observed points. Such error can be the result of imprecise measurements or observation bias.
Fortmann-Roe, Scott, Starfield, Richard, Getz, Wayne M   +2 more
openaire   +6 more sources

Aggressive prostate cancer is associated with pericyte dysfunction

Molecular Oncology, EarlyView.
Tumor‐produced TGF‐β drives pericyte dysfunction in prostate cancer. This dysfunction is characterized by downregulation of some canonical pericyte markers (i.e., DES, CSPG4, and ACTA2) while maintaining the expression of others (i.e., PDGFRB, NOTCH3, and RGS5).
Anabel Martinez‐Romero, Ane Martinez‐Larrinaga, Joaquim Grego‐Bessa, Saioa Garcia‐Longarte, Hielke van Splunder, Ianire Astobiza, Amaia Ercilla, Laura Bozal‐Basterra, Isabel Mendizabal, Pilar Villacampa, Arkaitz Carracedo, Mariona Graupera   +11 more
wiley   +1 more source

logcondens: Computations Related to Univariate Log-Concave Density Estimation

Journal of Statistical Software, 2011
Maximum likelihood estimation of a log-concave density has attracted considerable attention over the last few years. Several algorithms have been proposed to estimate such a density. Two of those algorithms, an iterative convex minorant and an active set
Lutz Dümbgen, Kaspar Rufibach
doaj  

Learning of Counting Crowded Birds of Various Scales via Novel Density Activation Maps

IEEE Access, 2020
The previous counting methods trained by the density map regression scheme fail to precisely count the number of birds in crowded bird images of various scales. This is due to the coarseness of the manually created target density maps.
Saehun Kim, Munchurl Kim
doaj   +1 more source

Nonparametric volatility density estimation

Bernoulli, 2003
We consider two kinds of stochastic volatility models. Both kinds of models contain a stationary volatility process, the density of which, at a fixed instant in time, we aim to estimate. We discuss discrete time models where for instance a log price process is modeled as the product of a volatility process and i.i.d. noise.
van Es, A.J., Spreij, P.J.C., van Zanten, J.H.   +2 more
openaire   +6 more sources

Detection of circulating tumor DNA in colorectal cancer patients using a methylation‐specific droplet digital PCR multiplex

Molecular Oncology, EarlyView.
We developed a cost‐effective methylation‐specific droplet digital PCR multiplex assay containing tissue‐conserved and tumor‐specific methylation markers. The assay can detect circulating tumor DNA with high accuracy in patients with localized and metastatic colorectal cancer.
Luisa Matos do Canto, Louise Raunkilde, Jan Lindebjerg, Mads Malik Aagaard, Christina Therkildsen, Jakob Kleif, Lars Henrik Jensen, Torben Frøstrup Hansen, Rikke Fredslund Andersen   +8 more
wiley   +1 more source

Densities and perceptions of jaguars in coastal Nayarit, Mexico

Wildlife Society Bulletin, 2016
Conservation of large carnivores will require greater analyses of population parameters, habitat use, and distribution in multiuse landscapes as human populations increase and agriculture expands.
Joe J. Figel, Fernando Ruíz‐Gutiérrez, David E. Brown   +2 more
doaj   +1 more source

Computational aspects of Bayesian spectral density estimation

, 2011
Gaussian time-series models are often specified through their spectral density. Such models present several computational challenges, in particular because of the non-sparse nature of the covariance matrix.
Chopin, Nicolas, Liseo, Brunero, Rousseau, Judith   +2 more
core   +5 more sources

Adaptive Kernel Density Estimation [PDF]

The Stata Journal: Promoting communications on statistics and Stata, 2003
This insert describes the module akdensity. akdensity extends the official kdensity that estimates density functions by the kernel method. The extensions are of two types: akdensity allows the use of an “adaptive kernel” approach with varying, rather than fixed, bandwidths; and akdensity estimates pointwise variability bands around the estimated ...
openaire   +3 more sources