Wavelets in functional data analysis: Estimation of multidimensional curves and their derivatives
نویسندگان
چکیده
A wavelet-based method is proposed to obtain accurate estimates of curves in more than one dimension and of their derivatives. By means of simulation studies, this novel method is compared to another locally-adaptive estimation technique for multidimensional functional data, based on free-knot regression splines. This comparison shows that the proposed method is particularly attractive when the curves to be estimated present strongly localized features. The multidimensional wavelet estimation method is thus applied to multilead electrocardiogram records, where strongly localized features are indeed expected.
منابع مشابه
Estimation of Climate Zone Effects on Iranian Temperature, Humidity, and Precipitation using Functional Analysis of Covariance
Functional Data Analysis (FDA) has recently made considerable progress because of easier access to the data that are essentially in the form of curves. Although functional modeling of Iranian precipitation based on temperature or humidity was done before, here we use functional analysis of variance and covariance to analyze the weather data collected randomly from Iranian weather stations in 20...
متن کاملWavelet Based Estimation of the Derivatives of a Density for a Discrete-Time Stochastic Process: Lp-Losses
We propose a method of estimation of the derivatives of probability density based on wavelets methods for a sequence of random variables with a common one-dimensional probability density function and obtain an upper bound on Lp-losses for such estimators. We suppose that the process is strongly mixing and we show that the rate of convergence essentially depends on the behavior of a special quad...
متن کاملWavelet Based Estimation of the Derivatives of a Density for m-Dependent Random Variables
Here, we propose a method of estimation of the derivatives of probability density based wavelets methods for a sequence of m−dependent random variables with a common one-dimensional probability density function and obtain an upper bound on Lp-losses for the such estimators.
متن کاملSome New Methods for Prediction of Time Series by Wavelets
Extended Abstract. Forecasting is one of the most important purposes of time series analysis. For many years, classical methods were used for this aim. But these methods do not give good performance results for real time series due to non-linearity and non-stationarity of these data sets. On one hand, most of real world time series data display a time-varying second order structure. On th...
متن کاملEstimation of Functional Derivatives
Situations of a functional predictor paired with a scalar response are increasingly encountered in data analysis. Predictors are often appropriately modeled as square integrable smooth random functions. Imposing minimal assumptions on the nature of the functional relationship, we aim at estimating the directional derivatives and gradients of the response with respect to the predictor functions....
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Computational Statistics & Data Analysis
دوره 56 شماره
صفحات -
تاریخ انتشار 2012