Pages that link to "Item:Q1896143"

The following pages link to A study of logspline density estimation (Q1896143):

Displaying 20 items.

• ACCURACY OF NONPARAMETRIC DENSITY ESTIMATION FOR UNIVARIATE GAUSSIAN MIXTURE MODELS: A COMPARATIVE STUDY (Q5016270) (← links)
• (Q5054660) (← links)
• Classification of flash crashes using the Hawkes<i>(p,q)</i>framework (Q5068081) (← links)
• Penalized log-density estimation using Legendre polynomials (Q5083902) (← links)
• Aggregated functional data model for near-infrared spectroscopy calibration and prediction (Q5130134) (← links)
• Functional Horseshoe Priors for Subspace Shrinkage (Q5146030) (← links)
• NONPARAMETRIC DENSITY ESTIMATION BY B-SPLINE DUALITY (Q5221310) (← links)
• Unsupervised learning of regression mixture models with unknown number of components (Q5222481) (← links)
• The endo–exo problem in high frequency financial price fluctuations and rejecting criticality (Q5234347) (← links)
• Modelling Directional Dispersion through Hyperspherical Log-Splines (Q5473057) (← links)
• Score-based causal learning in additive noise models (Q5739677) (← links)
• Spline local basis methods for nonparametric density estimation (Q6158228) (← links)
• Parallel Markov chain Monte Carlo for non-Gaussian posterior distributions (Q6538510) (← links)
• Appropriate use of parametric and nonparametric methods in estimating regression models with various shapes of errors (Q6548860) (← links)
• Identification of topology changes in power grids using phasor measurements (Q6571882) (← links)
• Statistical estimation in passenger-to-train assignment models based on automated data (Q6580704) (← links)
• Computation of the nonparametric maximum likelihood estimate of a univariate log-concave density (Q6600360) (← links)
• Likelihood ratio combination of multiple biomarkers via smoothing spline estimated densities (Q6618421) (← links)
• Estimating precipitation extremes using the log-histospline (Q6626076) (← links)
• Density Regression with Conditional Support Points (Q6631080) (← links)