Time Series Analysis
Concepts and Techniques for Community Practitioners
Bibliographic Data
| ID | 6076862 |
|---|---|
| Authors | Patrick Dattalo (0000-0002-6760-9035, Virginia Commonwealth University, corresponding author) |
| Year | 1998 |
| Volume | 5 |
| Issue | 4 |
| Pages | 67-85 |
| Publication date | 1998-09-30 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Community Practice (JOURNAL) |
| Journal identifiers | ISSN: 1070-5422 • E-ISSN: 1543-3706 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1300/j125v05n04_05 |
| OpenAlex | W1570281525 |
| Language | EN |
| Citations received | 1 |
| References cited | 8 |
This paper introduces community practitioners to important concepts and issues related to time series analysis. The basic components of a time series-trend, cycle, seasonal variation, and stochastic-are described, together with the related issues of sampling rate, autocorrelation, length, and missing observations. Then, a community practice example demonstrates the use of a basic two-step analytical technique. An understanding of these concepts and techniques can encourage practitioners to conduct preliminary analyses of time series, and help them evaluate the need for additional, more complex procedures
Autocorrelation · Data science · Econometrics · Machine learning · Management science · Missing data · Sampling (signal processing · Series (stratigraphy · Statistics · Time series · Variation (astronomy · Advanced Text Analysis Techniques · Computer Science · Engineering · Mathematics · Geology
| Unique citing works | 1 |
|---|---|
| Citations per year | 0,05 |
| Citation span | 2007 - 2007 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |