Search results for "Nonparametric"

Effect of diode laser irradiation on the attachment rate of periodontal ligament cells: an in vitro study.

2001

The present study is part of a basic research program investigating the cellular effects of an 810 nm GaAlAs-diode laser on human periodontal tissues. The aim of the investigation was to evaluate the effects of laser treatment of root surface specimens on the attachment of periodontal ligament (PDL) cells in vitro.Root specimens were prepared from periodontally diseased teeth. PDL cells were obtained from human third molar ligaments. Cells were cultured under simple, standardized, and reproducible experimental conditions. One hundred fifty root specimens were scaled and root planed with curets followed by air-powder abrasive treatment; 75 were then lased and 75 served as controls. The irrad…

Multivariate nonparametric tests in a randomized complete block design

2003

AbstractIn this paper multivariate extensions of the Friedman and Page tests for the comparison of several treatments are introduced. Related unadjusted and adjusted treatment effect estimates for the multivariate response variable are also found and their properties discussed. The test statistics and estimates are analogous to the traditional univariate methods. In test constructions, the univariate ranks are replaced by multivariate spatial ranks (J. Nonparam. Statist. 5 (1995) 201). Asymptotic theory is developed to provide approximations for the limiting distributions of the test statistics and estimates. Limiting efficiencies of the tests and treatment effect estimates are found in the…

Influence Functions and Efficiencies of k-Step Hettmansperger–Randles Estimators for Multivariate Location and Regression

2016

In Hettmansperger and Randles (Biometrika 89:851–860, 2002) spatial sign vectors were used to derive simultaneous estimators of multivariate location and shape. Oja (Multivariate nonparametric methods with R. Springer, New York, 2010) proposed a similar approach for the multivariate linear regression case. These estimators are highly robust and have under general assumptions a joint limiting multinormal distribution. The estimates are easy to compute using fixed-point algorithms. There are however no exact proofs for the convergence of these algorithms. The existence and uniqueness of the solutions also still remain unproven although we believe that they hold under general conditions. To ci…

Non-Parametric Rank Statistics for Spectral Power and Coherence

2019

AbstractDespite advances in multivariate spectral analysis of neural signals, the statistical inference of measures such as spectral power and coherence in practical and real-life scenarios remains a challenge. The non-normal distribution of the neural signals and presence of artefactual components make it difficult to use the parametric methods for robust estimation of measures or to infer the presence of specific spectral components above the chance level. Furthermore, the bias of the coherence measures and their complex statistical distributions are impediments in robust statistical comparisons between 2 different levels of coherence. Non-parametric methods based on the median of auto-/c…

Distribution Dynamics and Nonlinear Growth

2003

Non-parametric spectrum cartography using adaptive radial basis functions

2017

This paper presents a framework for spectrum cartography based on the use of adaptive Gaussian radial basis functions (RBF) centered around a specific number of centroid locations, which are determined, jointly with the other RBF parameters, by the available measurement values at given sensor locations in a specific geographical area. The spectrum map is constructed non-parametrically as no prior knowledge about the transmitters is assumed. The received signal power at each location (over a given bandwidth and time period) is estimated as a weighted contribution from different RBF, in such a way that the both RBF parameters and the weights are jointly optimized using an alternating minimiza…

How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study

2019

Abstract This paper replicates the Diebold and Yilmaz (2012) study on the connectedness of the commodity market and three other financial markets: the stock market, the bond market, and the FX market, based on the Generalized Forecast Error Variance Decomposition, GEFVD. We show that the net spillover indices (of directional connectedness), used to assess the net contribution of one market to overall risk in the system, are sensitive to the normalization scheme applied to the GEFVD. We show that, considering data generating processes characterized by different degrees of persistence and covariance, a scalar-based normalization of the Generalized Forecast Error Variance Decomposition is pref…

Visual aftereffects and sensory nonlinearities from a single statistical framework

2015

When adapted to a particular scenery our senses may fool us: colors are misinterpreted, certain spatial patterns seem to fade out, and static objects appear to move in reverse. A mere empirical description of the mechanisms tuned to color, texture, and motion may tell us where these visual illusions come from. However, such empirical models of gain control do not explain why these mechanisms work in this apparently dysfunctional manner. Current normative explanations of aftereffects based on scene statistics derive gain changes by (1) invoking decorrelation and linear manifold matching/equalization, or (2) using nonlinear divisive normalization obtained from parametric scene models. These p…

SM identification of approximating models forH∞ robust control

1999

Set Membership (SM) W, identification of mixed parametric and nonparametric models is investigated, aimed to estimate a low order approximating model and an identification error, giving a measure of the unmodeled dynamics in a form well suited for H, control methodologies. In particular, the problem of estimating the parameters of the parametric part and the H, bound on the modeling error is solved using frequency domain data, supposing lbo bounded measurement errors and exponentially stable unmodeled dynamics. The effectiveness of the proposed procedure is tested on some numerical examples, showing the advantages of the proposed methods over the existing nonparametric H, identification app…

Landmark identification on direct digital versus film-based cephalometric radiographs: A human skull study

2002

The purpose of this study was to investigate differences in landmark identification on vertically scanned, direct digital and conventional (18 x 24 cm) cephalometric radiographs. Eight observers, all orthodontists or postgraduate orthodontic students, recorded 6 landmarks twice on 3 digital and 3 conventional cephalograms obtained from 3 human skulls in a standardized fashion. Digital images were displayed on a 15.1-in TFT monitor in 3:1 mode (20 x 26 cm). Recordings were transferred into standardized coordinate systems and evaluated separately for each coordinate. After correcting for magnification, precision was assessed with Maloney-Rastogi tests, and intraobserver and interobserver repr…