When spatial data are correlated, currently available data-driven smoothing parameter selection methods for nonparametric regression will often fail to provide useful results. The authors propose a method that adjusts the generalized cross-validation criterion effect of correlation in case bivariate local polynomial regression. Their approach uses pilot fit and estimation parametric covariance model. is easy implement leads improved selection, even when model misspecified. methodology...

Summary Field studies were conducted to determine the potential of multispectral classification late‐season grass weeds in wheat. Several techniques have been used discriminate differences reflectance between wheat and Avena sterilis , Phalaris brachystachys Lolium rigidum Polypogon monspeliensis 400–900 nm spectrum, evaluate accuracy performance for a spectral signature into plant species or group which it belongs. Fisher’s linear discriminant analysis, nonparametric functional analysis...

The TTS package has been developed in R software to predict the mechanical properties of viscoelastic materials, at short and long observation times/frequencies by applying Time Temperature Superposition (TTS) principle. is a physical principle used material science estimate beyond experimental range observed shifting data curves obtained other temperatures relative reference temperature dataset. It methodology related accelerated life-tests reliability, whereas library one first open source...

Abstract. Systematic sampling is frequently used in surveys, because of its ease implementation and design efficiency. An important drawback systematic sampling, however, that no direct estimator the variance available. We describe a new model‐based expectation variance, under non‐parametric model for population. The sufficiently flexible it can be expected to hold at least approximately many situations with continuous auxiliary variables observed population level. prove consistency both...

Abstract Consider the fixed regression model where error random variables are coming from a strictly stationary, non-white noise stochastic process. In situation like this, automated bandwidth selection methods for non-parametric break down. We present plug-in method choosing smoothing parameter local least squares estimators of function. The takes presence correlated errors explicitly into account through parametric correlation function specification. theoretical performance linear...

SUMMARY Hydrothermal time (HTT) is a valuable environmental synthesis to predict weed emergence. However, scientists face practical problems in determining the best soil depth at which calculate it. Two different types of measures are proposed for this: moment-based indices and probability density-based indices. Due monitoring process, it not possible observe exact emergence every seedling; therefore, times observed individually, seedling by seedling, but an aggregated way. To address these...

Abstract Background Predictive microbiology develops mathematical models that can predict the growth rate of a microorganism population under set environmental conditions. Many primary have been proposed. However, when are applied to bacterial curves, biological variability is reduced single curve defined by some kinetic parameters (lag time and rate), sometimes give poor fits in regions curve. The development prediction band (from curves) using non-parametric bootstrap methods permits...

In this paper, we study the nonparametric estimation of regression function and its derivatives using weighted local polynomial fitting. Consider fixed model suppose that random observation error is coming from a strictly stationary stochastic process. Expressions for bias variance array estimators are obtained joint asymptotic normality established. The influence dependence data observed in expression variance. We also propose variable bandwidth selection procedure. A simulation an analysis...

This work addresses the problem of supervised classification industrial wood species (seven different types in present study) through their thermo‐oxidative stability. is evaluated by pressure differential scanning calorimetry (PDSC) using ASTM E2009. The maximization ratio correct and reduction costs this activity are intended. was carried out two proposals: applying novel nonparametric functional data analysis techniques, based on kernel estimation, to original PDSC curves, machine...

This article describes a free, open-source collection of templates for the popular Excel (2013, and later versions) spreadsheet program. These are files that allow easy intuitive learning implementation practical examples concerning descriptive statistics, random variables, confidence intervals, hypothesis testing. Although they designed to be used with Excel, can also employed other free programs (changing some particular formulas). Moreover, we exploit possibilities ActiveX controls...

Interval-grouped data are defined, in general, when the event of interest cannot be directly observed and it is only known to have been occurred within an interval. In this framework, a nonparametric kernel density estimator proposed studied. The approach based on classical Parzen–Rosenblatt generalisation binned estimator. asymptotic bias variance derived under usual assumptions, effect using non-equally spaced grouped analysed. Additionally, plug-in bandwidth selector proposed. Through...

Summary Parametric nonlinear regression ( PNR ) models are used widely to fit weed seedling emergence patterns soil microclimatic indices. However, such approximation has been questioned, mainly due several statistical limitations. Alternatively, nonparametric approaches can be overcome the problems presented by models. Here, we an data set of Phalaris paradoxa compare both approaches. Mean squared error and correlation results indicated higher accuracy for descriptive ability but similar...

Nonparametric regression estimation is a powerful tool to handle multidimensional data. When dependent data set analyzed, classical techniques need be modified provide useful results. In this work, different approximations take the spatial dependence into account are exposed. A bandwidth selection technique that adjusts generalized cross‐validation criterion for effect of correlation, in case bivariate local polynomial regression, considered. Moreover, bootstrap algorithm designed assess...