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Inference for modulated stationary processes
Zhibiao Zhao
, Xiaoye Li
Statistics
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peer-review
13
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Dive into the research topics of 'Inference for modulated stationary processes'. Together they form a unique fingerprint.
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Mathematics
Stationarity
100%
Stationary Process
100%
Variance
50%
Simulation Study
50%
Bootstrapping
50%
Inferential Statistics
50%
Real Data
50%
Central Limit Theorem
50%
Variance Estimation
50%
Stationary Time Series
50%
Cumulative Sum
50%
Monte Carlo Method
50%
Keyphrases
Stationary Process
100%
Self-normalization
100%
Growth Rate
16%
Monte Carlo Simulation Study
16%
Proposed Methodology
16%
Statistical Inference
16%
Precipitation Rate
16%
Non-stationarity
16%
Normalization Method
16%
Stationarity
16%
Mean Annual Precipitation
16%
Central Limit Theorem
16%
Seoul
16%
Long-run Variance Estimation
16%
Gross National Product
16%
Wild Bootstrap
16%
Locally Stationary Time Series
16%
Inference Problem
16%
Change-point Problem
16%
Product Growth
16%
Cumulative Sum Test
16%
Economics, Econometrics and Finance
Measure of Dispersion
100%
Monte Carlo Simulation
50%
Time Series
50%
National Income
50%
United States of America
50%