Search results for " smoothing"
showing 7 items of 47 documents
The Induced Smoothed lasso: A practical framework for hypothesis testing in high dimensional regression.
2020
This paper focuses on hypothesis testing in lasso regression, when one is interested in judging statistical significance for the regression coefficients in the regression equation involving a lot of covariates. To get reliable p-values, we propose a new lasso-type estimator relying on the idea of induced smoothing which allows to obtain appropriate covariance matrix and Wald statistic relatively easily. Some simulation experiments reveal that our approach exhibits good performance when contrasted with the recent inferential tools in the lasso framework. Two real data analyses are presented to illustrate the proposed framework in practice.
Estimation of total electricity consumption curves by sampling in a finite population when some trajectories are partially unobserved
2019
International audience; Millions of smart meters that are able to collect individual load curves, that is, electricity consumption time series, of residential and business customers at fine scale time grids are now deployed by electricity companies all around the world. It may be complex and costly to transmit and exploit such a large quantity of information, therefore it can be relevant to use survey sampling techniques to estimate mean load curves of specific groups of customers. Data collection, like every mass process, may undergo technical problems at every point of the metering and collection chain resulting in missing values. We consider imputation approaches (linear interpolation, k…
The Euro Area Crisis; Need for a Supranational Fiscal Risk Sharing Mechanism?
2013
The aim of this paper is to assess the effectiveness of risk sharing mechanisms in the euro area and whether a supranational fiscal risk sharing mechanism could insure countries against very severe downturns. Using an unbalanced panel of 15 euro area countries over the period 1979â2010, the results of the paper show that: (i) the effectiveness of risk sharing mechanisms in the euro area is significantly lower than in existing federations (such as the U.S. and Germany) and (ii) it falls sharply in severe downturns just when it is needed most; (iii) a supranational fiscal stabilization mechanism, financed by a relatively small contribution, would be able to fully insure euro area countries …
Computational Techniques for the Analysis of Small Signals in High-Statistics Neutrino Oscillation Experiments
2020
The current and upcoming generation of Very Large Volume Neutrino Telescopes – collecting unprecedented quantities of neutrino events – can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the neutrino mass ordering. The sensitivity of an experiment to these effects can be estimated from Monte Carlo simulations. With the high number of events that will be collected, there is a trade-off between the computational expense of running such simulations and the inherent statistical uncertainty in the determined values. In such a scenario, it becomes impractical to produce and use adequately-sized sets of simulated events with traditional methods, such as M…
Fast Computation by Subdivision of Multidimensional Splines and Their Applications
2016
We present theory and algorithms for fast explicit computations of uni- and multi-dimensional periodic splines of arbitrary order at triadic rational points and of splines of even order at diadic rational points. The algorithms use the forward and the inverse Fast Fourier transform (FFT). The implementation is as fast as FFT computation. The algorithms are based on binary and ternary subdivision of splines. Interpolating and smoothing splines are used for a sample rate convertor such as resolution upsampling of discrete-time signals and digital images and restoration of decimated images that were contaminated by noise. The performance of the rate conversion based spline is compared with the…
Adaptive smoothing spline using non-convex penalties
2022
We propose a new adaptive penalty for smoothing via penalized splines. The new form of adaptive penalization is based on penalizing the differences of the coefficients of adjacent bases, using non-convex penalties. This makes possible to estimate curves with varying amounts of smoothness. Comparisons with respect to some competitors are presented.
The induced smoothed LASSO
2016
We propose a new lasso-type estimator of regression coefficients for regression models. Our proposal relies on the recent idea of induced smoothing and leads to estimators with sampling distribution somewhat close to the Normal one, regardless of their true value, along with the corresponding reliable covariance matrix. As a consequence inference (e.g. p-values) may be carried out relatively easily. We present results from some simulation experiments.