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作者：STANISWALIS, JG; SEVERINI, TA
作者单位：Northwestern University
摘要：We concern ourselves with diagnostics for checking the overall and local goodness of fit of a model s(x) used in the regression of Y on x is-an-element-of U = [0, 1]d. The model for s(x) is a functional form that depends on a finite number of unknown parameters. Two statistics, LAMBDA and LAMBDA-w, are proposed that measure the level of agreement between the model fit to the data and the nonparametric kernel estimator on m preselected points in U. Conditions are given under which LAMBDA and LA...
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作者：BRADLEY, RA; STEWART, FP
摘要：A multidimensional block design (MBD) is an amalgamation of d < 1 component block designs. It may be represented as a d-dimensional lattice with b* = PI-s = 1d b(s) nodes, where b(s) is the number of blocks in the sth component block design. The (j1, ..., j(d))-node of the lattice may have h(i, j1, ..., j(d)) greater-than-or-equal-to 0 experimental units assigned to treatment i, i = 1, ..., nu, j(s) = 1, ..., b(s), s = 1, ..., d, where nu is the number of treatments. If each node of the lattic...
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作者：PEPE, MS
摘要：Kaplan-Meier and cumulative incidence functions are not sufficient descriptive devices for studies that have multiple time-to-event endpoints. For example, in cancer treatment research the probability of tumor recurrence conditional on not having died from treatment-related toxicities and the prevalence of graft-versus-host disease among leukemia-free patients surviving a bone marrow transplant are of interest. These quantities can be estimated nonparametrically using simple functions of sever...
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作者：GUTTORP, P; THOMPSON, ML
作者单位：University of Cape Town
摘要：To study patterns of volcanicity it is important to use historical data. These data are, however, frequently incomplete. We develop a nonparametric procedure for estimating second-order parameters of the point process of eruption starts from a catalog. This method requires an assumption of underlying stationarity, of smoothness of the probability of recording an eruption as a function of time, and of independence of this probability from the history of the process. We illustrate the procedure ...
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作者：DIEBOLD, FX; RUDEBUSCH, GD
作者单位：Federal Reserve System - USA; Federal Reserve System Board of Governors
摘要：We examine the ability of the composite index of leading economic indicators to predict future movements in aggregate economic activity. Previous examinations of predictive performance have evaluated either the in-sample residual errors from a forecasting equation fitted to the entire sample of data or the out-of-sample forecast errors from an equation fitted to a subsample of the data. Unlike previous evaluations, we perform a real-time analysis, which uses the provisional and partially revis...
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作者：SPEED, TP
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作者：HOCKING, RR
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作者：MAGEE, L; BURBIDGE, JB; ROBB, AL
摘要：Quantiles of a variable Y conditional on another variable X, when plotted against X, can be a useful descriptive tool. These plots give a quick impression of the functional form of the relation between X and the location, spread, and shape of the conditional distribution of Y. If several Y are observed for each X, then sample quantiles could be calculated for each X. The resulting quantile plot may be quite noisy, however, and smoothing across X may be desired. This article presents an algorit...
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作者：HALL, P; WEHRLY, TE
作者单位：Commonwealth Scientific & Industrial Research Organisation (CSIRO); Texas A&M University System; Texas A&M University College Station
摘要：We introduce a simple geometric method for removing edge effects from kernel-type nonparametric regression estimators. It involves reflecting the data set in two estimated points, thereby generating a new data set with three times the range of the original data. The usual kernel-type estimator may be applied to the new, enlarged data set, without any danger of edge effects. This technique is applicable generally to both regularly spaced and randomly spaced designs and admits a natural analog o...
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作者：OSULLIVAN, F
作者单位：University of Washington; University of Washington Seattle
摘要：An approach to multidimensional smoothing is introduced that is based on a penalized likelihood with a modified discretized Laplacian penalty term. The choice of penalty simplifies computational difficulties associated with standard multidimensional Laplacian smoothing methods yet without compromising mean squared error characteristics, at least on the interior of the region of interest. For linear smoothing in hyper-rectangular domains, which has wide application in image reconstruction and r...
