Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 24 for “"Confidence bands"”.
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Sequential confidence bands for densities
… procedure for constructing a fixed width confidence band for an unknown density on a finite interval and show the procedure has the desired coverage probability asymptotically as the width of the band approaches zero. The procedure is based on a result of Bickel and Rosenblatt (1973, Ann. …
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Simultaneous confidence bands in linear regression analysis
A simultaneous confidence band provides useful information on the plausible range of an<br/>unknown regression model. For a simple linear regression model, the most frequently<br/>quoted bands in the statistical literature include the two-segment band, the three-segment<br/>band and the hyperbolic …
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Confidence bands for survival functions under semiparametric random censorship models
In medical reports point estimates and pointwise confidence intervals of parameters are usually displayed. When the parameter is a survival function, however, the approach of joining the upper end points of individual interval estimates obtained at several points and likewise for the lower end …
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Confidence bands for survival curves using model assisted cox regression
… informative subject-specific simultaneous confidence bands (SCBs) for survival functions from right censored data. The approach is based on an extension of semiparametric random censorship models (SRCMs) to Cox regression, which produces reliable and more informative SCBs. SRCMs derive …
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Confidence bands, measurement noise, and multiple input - multiple output measurements using three-channel frequency response function estimator
… FRF magnitude variance estimates allow ’confidence bands’ to be placed on FRF magnitude estimates, giving an indication of the variability of the result. Uncorrelated content estimates indicate sources and magnitudes of noise in the measurement system. Both Monte Carlo simulations and …
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Methods for two-sample comparisons from censored time-to-event data
… their difference, accompanied by simultaneous confidence bands (SCBs). Alternatively, or in addition, one may conduct hypothesis testing for the difference of the two survival functions. The first project exploits two bootstrap methods to develop new Wald-type SCBs for the difference of …
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Quantile-based methods for prediction, risk measurement and inference
… problem is that of constructing simultaneous confidence bands for quantile regression functions when the predictor variables are constrained within a region is considered. In this context, a method is introduced that makes use of the asymmetric Laplace errors in conjunction with a simulation …
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Analysis Using Smoothing Via Penalized Splines as Implemented in LME() in R
… The second example also demonstrates how to fit confidence bands to the three-group model. The examples use mixed model software as implemented in lme() in R. Following the examples a discussion of the method is presented.
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Model Selection, Uniform Inference and Nonparametric Regression
… chapter in order to construct valid uniform confidence bands for the series estimator. The uniform confidence bands are valid in the sense that they control the asymptotic size for the conditional mean function, or its linear functionals, seen as a process in the covariates and the models …
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Ranking of Fatigue Data Based upon Monte Carlo Simulated Confidence Number Figures
… were used to generate L10 lives. A model of confidence number was developed dependent upon statistically large samples of simulated L10 fatigue lives, and independent of a limited number of published curves. Using these simulated values, Confidence number figures were generated that deviated …
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Quantile regression and survival analysis
… direct use of regression quantiles to construct confidence intervals and confidence bands for conditional quantiles and prediction intervals for future response variables under homoscedastic linear models and heteroscedastic linear models is proposed. Comparison of the direct method with the …
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Essays on Algorithmic Learning and Uncertainty Quantification
… which is then applied to construct uniform confidence bands for the widely-used kernel ridge regression algorithm. The third and final essay, titled “Frank-Wolfe Meets Metric Entropy,” uses ideas from asymptotic geometry to derive new dimension-dependent and domain-specific lower bounds for …
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An Investigation into Classification of High Dimensional Frequency Data
… estimates, correlation coefficients, and confidence bands. Related work included considering ways to recover and exploit certain symmetry characteristics of the objects (using the response data). Present investigations are not entirely conclusive, but the correlation coefficient classifier …
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Quantile Inference and Change Point Test under Time Series Non-stationarity
… the latter theoretical results, simultaneous confidence bands for the above mentioned quantile curves with asymptotically correct coverage probabilities are constructed. The second part of the thesis considers quantile structural change testing for linear models with random designs and a wide …
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Parametric quantile regression based on the generalised gamma distribution
… theory for obtaining the expressions for confidence bands around them is given. Based on the chi-square goodness-of-fit test, we suggest a test statistic that checks the goodness of the generalised gamma model for given data. We validate the whole theoretical process computationally via …
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Bias Assessment and Reduction in Kernel Smoothing
… data. In this dissertation, we propose pointwise confidence intervals for bias and demonstrate a software tool to implement the confidence bands in practice. The effectiveness of the proposed bias assessment tool is demonstrated using simulated data and is illustrated by its application to …
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On Wavelet-Based Methods for Scalar-on-Function Regression
… a technique for constructing non-parametric confidence bands, demonstrate the performance of our methods through extensive simulations, and apply them to real data in order to investigate the relationship between fractional anisotropy profiles and cognitive function in subjects with multiple …
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Three essays on long memory tests for persistence in volatility and structural vector autoregression modeling of real exchange rates
… framework with long run restrictions. Confidence bands do not find significant impulse responses and the signs of the estimated impulse responses are very sensitive to the lag selection criteria adopted. Possible cointegration effects seem to be the main driving force behind the …
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Testing the Assumption of Sample Invariance of Item Difficulty Parameters in the Rasch Rating Scale Model
… variation: (a) the between-fit statistic, (b) confidence intervals around the mean of the estimates and (c) a general linear model. The general linear model used the person residual statistic from the Winsteps' person output file as a dependent variable with year, gender and type of major as …
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Non-asymptotic bounds for prediction problems and density estimation.
This dissertation investigates the learning scenarios where a high-dimensional parameter has to be estimated from a given sample of fixed size, often smaller than the dimension of the problem. The first part answers some open questions for the binary classification problem in the framework of …
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