Periodograms & times Series
نویسنده
چکیده
2017 1. Using information given in appendix A, identify with the periodogram the period of the main seasonal pattern in the time series beer 1. 2. Using information given in appendix B, identify with the periodogram the period of the main seasonal pattern in the time series airpass. 3. Explain R code in appendices A and B. 1 time series are taken from the R package fma, and R outputs are shown in appendices.
منابع مشابه
Multiscale and multilevel technique for consistent segmentation of nonstationary time series
In this paper, we propose a fast, well-performing, and consistent method for segmenting a piecewise-stationary, linear time series with an unknown number of breakpoints. The time series model we use is the nonparametric Locally Stationary Wavelet model, in which a complete description of the piecewise-stationary second-order structure is provided by wavelet periodograms computed at multiple sca...
متن کاملMultiple change-point detection for high-dimensional time series via Sparsified Binary Segmentation
Time series segmentation, a.k.a. multiple change-point detection, is a well-established problem. However, few solutions are designed specifically for high-dimensional situations. In this paper, our interest is in segmenting the second-order structure of a high-dimensional time series. In a generic step of a binary segmentation algorithm for multivariate time series, one natural solution is to c...
متن کاملSTT-Research Memoranda #693 On asymptotic distributions of weighted sums of periodograms
We establish asymptotic normality of weighted sums of periodograms of a stationary linear process where weights depend on the sample size. Such sums appear in numerous statistical applications and can be regarded as a discretized versions of the quadratic forms involving integrals of weighted periodograms. Conditions for asymptotic normality of these weighted sums are simple and resemble Lindeb...
متن کاملAsymptotic Spectral Theory for Nonlinear Time
We consider asymptotic problems in spectral analysis of stationary causal processes. Limiting distributions of periodograms and smoothed periodogram spectral density estimates are obtained and applications to the spectral domain bootstrap are given. Instead of the commonly used strong mixing conditions, in our asymptotic spectral theory we impose conditions only involving (conditional) moments,...
متن کاملAsymptotic Spectral Theory for Nonlinear Time Series 1
Abstract: We consider asymptotic problems in spectral analysis of stationary causal processes. Limiting distributions of periodograms and smoothed periodogram spectral density estimates are obtained and applications to spectral domain bootstrap are made. Instead of the commonly used strong mixing conditions, in our asymptotic spectral theory we impose conditions only involving (conditional) mom...
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:
دوره شماره
صفحات -
تاریخ انتشار 2017