Results 11 to 20 of about 7,325 (196)
kamila: Clustering Mixed-Type Data in R and Hadoop
Journal of Statistical Software, 2018 In this paper we discuss the challenge of equitably combining continuous (quantitative) and categorical (qualitative) variables for the purpose of cluster analysis. Existing techniques require strong parametric assumptions, or difficult-to-specify tuning
Alexander H. Foss, Marianthi Markatou
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Right-Censored Time Series Modeling by Modified Semi-Parametric A-Spline Estimator
Entropy, 2021 This paper focuses on the adaptive spline (A-spline) fitting of the semiparametric regression model to time series data with right-censored observations.
Dursun Aydın +2 more
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THE APPLICATION OF THE SEMIPARAMETRIC GSTAR MODEL IN DETERMINING GAMMA-RAY LOG DATA ON SOIL LAYERS
Media Statistika, 2022 This research examines the semiparametric Generalized Space-Time Autoregressive (GSTAR) spacetime modeling and determines its spatial weight. In general, the spatial weights used are uniform, binary weights, and based on the distance, the result is a ...
Yundari Yundari, Shantika Martha
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Semiparametric Regression Pursuit [PDF]
Statistica Sinica, 2012 The semiparametric partially linear model allows flexible modeling of covariate effects on the response variable in regression. It combines the flexibility of nonparametric regression and parsimony of linear regression. The most important assumption in the existing methods for the estimation in this model is to assume a priori that it is known which ...
Jian, Huang, Fengrong, Wei, Shuangge, Ma
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Remote Sensing, 2021 Airborne laser scanning (ALS) acquisitions provide piecemeal coverage across the western US, as collections are organized by local managers of individual project areas.
Francisco Mauro +7 more
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On a Problem in Semiparametric Estimation [PDF]
, 1991 The estimation problem in a semiparametric model, namely, the generalized Lehmann alternative model, is considered here. Suppose that two independent samples X1,…,Xm and Y1, …,Yn with d.f.’s F and G, respectively, are observed. Assume that G(·)=H(F(·);θ), where the form of the function H is known, but F and the parameter θ are unknown.
JAMMALAMADAKA, SR, WAN, X
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A General Nonlinear Multilevel Structural Equation Mixture Model
Frontiers in Psychology, 2014 In the past 2 decades latent variable modeling has become a standard tool in the social sciences. In the same time period, traditional linear structural equation models have been extended to include nonlinear interaction and quadratic effects (e.g ...
Augustin eKelava, Holger eBrandt
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ESTIMASI PARAMETER COX SEMIPARAMETRIC HAZARDS MODEL DENGAN METODE EFRON PADA DATA TERSENSOR KANAN
Jurnal Matematika UNAND, 2021 Salah satu kendala yang sering dihadapi pada penelitian survival adalah adanya data tersensor. Jika data tersensor dihilangkan, maka akan terjadi bias. Pengolahan data tersensor dapat dilakukan dengan Cox Semiparametric Hazards model. Pada penelitian ini,
TEDY MACHMUD +3 more
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Semiparametric Wavelet-Based JPEG IV Estimator for Endogenously Truncated Data
IEEE Access, 2019 A new and an enriched JPEG algorithm is provided for identifying redundancies in a sequence of irregular noisy data points which also accommodates a reference-free criterion function.
Nir Billfeld, Moshe Kim
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The influence function of semiparametric estimators [PDF]
Quantitative Economics, 2015 There are many economic parameters that depend on nonparametric first steps. Examples include games, dynamic discrete choice, average exact consumer surplus, and treatment effects. Often estimators of these parameters are asymptotically equivalent to a sample average of an object referred to as the influence function.
Hidehiko Ichimura, Whitney K. Newey
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