Spectral Analysis of Time-series Data

Technometrics ◽  
2004 ◽  
Vol 46 (4) ◽  
pp. 497-498
Author(s):  
Eric R Ziegel
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Analysis Of Time Series

scholarly journals PERAMALAN CURAH HUJAN MENGGUNAKAN METODE ANALISIS SPEKTRAL

2016 ◽  
Vol 5 (4) ◽  
pp. 183
Author(s):  
NI PUTU MIRAH SRI WAHYUNI ◽  
I WAYAN SUMARJAYA ◽  
I GUSTI AYU MADE SRINADI
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Time Series Data ◽  
Complete Information ◽  
Series Data ◽  
Analysis Method ◽  
Maximum Rainfall ◽  
Spectral Analysis Method ◽  
Large Peak ◽  
Analysis Of Time Series

The purpose of this research is the model of forecasting rainfall using spectral analysis method. To obtain complete information on characteristics of time series data we need to examine periodicity of the data. Examining the periodicity of time series data in the frequency domain is called spectral analysis. The results of spectral analysis show that periodogram is clearly dominated by a very large peak at frequency . This frequency corresponds to period of 12 cycle per month. Based on the results of analysis of time series data rainfall is SARIMA (0,1,1)(0,1,1)12 where the model can be written as The result indicates minimum rainfall happen in January and maximum rainfall happen in August.

Maximum Entropy Spectral Analysis of Time-Series Data from Combustion MHD Plasma

1985 ◽  
Vol 24 (Part 1, No. 9) ◽  
pp. 1204-1211 ◽  
Author(s):  
Tadashi Seidou ◽  
Yoshiaki Aoki ◽  
Norio Ohtomo
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Maximum Entropy ◽  
Time Series Data ◽  
Series Data ◽  
Maximum Entropy Spectral Analysis ◽  
Analysis Of Time Series

Comprehensive Spectral Analysis of Time Series Data of Recurrent Epidemics

1997 ◽  
Vol 36 (Part 1, No. 3A) ◽  
pp. 1303-1318 ◽  
Author(s):  
Ayako Sumi ◽  
Norio Ohtomo ◽  
Yukio Tanaka ◽  
Akio Koyama ◽  
Kazuo Saito
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Analysis Of Time Series

scholarly journals The bird's ear view of space physics: Audification as a tool for the spectral analysis of time series data

2014 ◽  
Vol 119 (7) ◽  
pp. 5259-5271 ◽  
Author(s):  
Robert L. Alexander ◽  
Sile O'Modhrain ◽  
D. Aaron Roberts ◽  
Jason A. Gilbert ◽  
Thomas H. Zurbuchen
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Time Series Data ◽  
Space Physics ◽  
Series Data ◽  
Analysis Of Time Series

scholarly journals SPAN: An interactive BASIC program for spectral analysis of time-series data

1980 ◽  
Vol 12 (3) ◽  
pp. 389-390
Author(s):  
Rebecca M. Warner ◽  
Paul G. Neumann
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Time Series Data ◽  
Basic Program ◽  
Series Data ◽  
Analysis Of Time Series

scholarly journals Assessing Stream-Aquifer Connectivity in a Coastal California Watershed

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 416
Author(s):  
Bwalya Malama ◽  
Devin Pritchard-Peterson ◽  
John J. Jasbinsek ◽  
Christopher Surfleet
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Water Level ◽  
Time Series Data ◽  
Series Data ◽  
Low Permeability ◽  
Pumping Tests ◽  
Stream Flows ◽  
The Impact

We report the results of field and laboratory investigations of stream-aquifer interactions in a watershed along the California coast to assess the impact of groundwater pumping for irrigation on stream flows. The methods used include subsurface sediment sampling using direct-push drilling, laboratory permeability and particle size analyses of sediment, piezometer installation and instrumentation, stream discharge and stage monitoring, pumping tests for aquifer characterization, resistivity surveys, and long-term passive monitoring of stream stage and groundwater levels. Spectral analysis of long-term water level data was used to assess correlation between stream and groundwater level time series data. The investigations revealed the presence of a thin low permeability silt-clay aquitard unit between the main aquifer and the stream. This suggested a three layer conceptual model of the subsurface comprising unconfined and confined aquifers separated by an aquitard layer. This was broadly confirmed by resistivity surveys and pumping tests, the latter of which indicated the occurrence of leakage across the aquitard. The aquitard was determined to be 2–3 orders of magnitude less permeable than the aquifer, which is indicative of weak stream-aquifer connectivity and was confirmed by spectral analysis of stream-aquifer water level time series. The results illustrate the importance of site-specific investigations and suggest that even in systems where the stream is not in direct hydraulic contact with the producing aquifer, long-term stream depletion can occur due to leakage across low permeability units. This has implications for management of stream flows, groundwater abstraction, and water resources management during prolonged periods of drought.

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