Applied time series analysis for managerial forecasting:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Oakland, Calif.
Holden-Day
1973
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIV, 231 S. graph. Darst. |
| ISBN: | 0816263663 |
Internformat
MARC
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| 100 | 1 | |a Nelson, Charles R. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Applied time series analysis for managerial forecasting |
| 264 | 1 | |a Oakland, Calif. |b Holden-Day |c 1973 | |
| 300 | |a XIV, 231 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 4 | |a Análisis de series cronológicas | |
| 650 | 7 | |a Bedrijfsbeleid |2 gtt | |
| 650 | 7 | |a Prognoses |2 gtt | |
| 650 | 4 | |a Prévision commerciale | |
| 650 | 4 | |a Série chronologique | |
| 650 | 7 | |a Wiskundige methoden |2 gtt | |
| 650 | 4 | |a Business forecasting | |
| 650 | 4 | |a Time-series analysis | |
| 650 | 0 | 7 | |a Zeitreihenanalyse |0 (DE-588)4067486-1 |2 gnd |9 rswk-swf |
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Datensatz im Suchindex
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|---|---|
| adam_text | Contents
1
FORECASTING METHODS AND OBJECTIVES 1
1.1 A Typology of Forecasting Methods, 1
Subjective Forecasting, 1
Structural and Econometric Models, 2
Deterministic Models, 4
Ad Hoc Forecasting Formulas, 6
Time Series Analysis, 7
1.2 Why Does Good Forecasting Pay Off? 11
1.3 The Relationship between the Forecaster and the
Decision maker, 14
FUNDAMENTAL CONCEPTS IN TIME
SERIES ANALYSIS 18
2.1 The Concept of Stationarity, 19
2.2 Autocorrelation, 23
2.3 Estimation of the Autocorrelation Function
from Sample Data, 27
2.4 Analysis of Nonstationary Time Series, 27
MODELS FOR STATIONARY TIME SERIES 30
3.1 Discrete Linear Stochastic Processes, 30
3.2 Moving average Processes, 33
The First order Moving average Process, 33
Moving average Processes of Higher Order, 36
3.3 Autoregressive Processes, 37
The First order Autoregression, 38
The Second order Autoregression, 43
Autoregressive Processes of Higher Order, 45
3.4 Invertibility of Moving average Processes, 46
3.5 Mixed Autoregressive Moving average Processes, 47
The ARMA (1,1) Process, 47
Mixed Processes of Higher Order, 52
4
MODELS FOR NONSTATIONARY TIME
SERIES 56
4.1 Differencing and Homogeneous Nonstationarity, 57
4.2 Other Transformations Useful in Achieving
Stationarity, 58
4.3 The Difference equation Form of the ARIMA
Process, 59
4.4 The Random shock Form of the ARIMA Process, 60
4.5 The Inverted Form of the ARIMA Process, 61
4.6 Constant Terms in ARIMA Processes, 63
4.7 Examples of Nonstationary Processes: Gross National
Product and Expenditure on Producers Durables, 64
IDENTIFICATION AND ESTIMATION
OF ARIMA MODELS 69
5.1 Estimation of the Autocorrelation Function, 70
xii contents
5.2 Determining the Appropriate Degree of Differencing,
75
5.3 Example: Expenditures on Producers Durables, 77
5.4 Identification of the Order of an Autoregressive
Process: The Partial Autocorrelation Function, 82
5.5 Example: Gross National Product, 84
5.6 Identification of Mixed Processes, 84
5.7 Preliminary Estimates of Parameters, 89
5.8 Maximum likelihood Estimation of ARIMA Models,
92
5.9 Statistical Inference: Standard Errors for Maximum
likelihood Estimates, 97
5.10 Examples of Estimation Using Program
ESTIMATE, 99
5.11 Diagnostic Checks, 107
5.12 Additional Examples: Tool Sales Series A and B
and the Unemployment Rate, 116
Tool Sales Series A, 116
Tool Sales Series B, 116
The Unemployment Rate, 129
6
FORECASTING ARIMA PROCESSES 143
6.1 Minimum Mean square error Forecasts, 143
6.2 Computation of Conditional Expectation Forecasts,
144
One step ahead Forecasts, 144
Multistep ahead Forecasts, 146
Limiting Properties of Forecast Profiles
for Stationary Models, 147
6.3 Examples of Forecast Profiles for Stationary
Processes, 148
6.4 Examples of Forecast Profiles for Nonstationary
Processes, 149
6.5 Adaptive Forecasting, 157
6.6 The Dispersion of Forecast Errors: Variance, Standard
Deviation, and Confidence Intervals, 159
6.7 Forecasting after Transformation to Logs, 161
The Log normal Distribution, 162
Application to Forecasting, 163
contents xiii
7
MODELS FOR SEASONAL TIME SERIES 168
7.1 The Seasonal Moving average Process, 169
7.2 The Seasonal Autoregressive Process, 171
7.3 The Seasonal Integrated Autoregressive Moving
average Model, 173
7.4 The General Multiplicative Seasonal Model, 174
Seasonal Adjustment: An Alternative View, 174
Autocorrelation Structure of the Multiplicative
Seasonal Process, 175
7.5 Identification, Estimation, and Forecasting of the
Multiplicative Seasonal Model: The Example
of Monthly Automobile Registrations, 177
Identification, 177
Estimation, 187
Diagnostic Checks, 187
Forecasting, 194
8
FORECAST EVALUATION: A CASE STUDY 202
8.1 The Federal Reserve Board MIT Penn (FMP)
Model of the United States Economy, 203
8.2 ARIMA Models for 14 Endogenous Variables of the
FMP Model, 204
8.3 Analysis of Sample period Prediction Errors, 205
8.4 Turning point Errors, 211
8.5 Composite Predictions for the Endogenous Variables,
211
8.6 Jointly Optimal Composite Predictions, 215
8.7 Analysis of Postsample Prediction Errors, 217
Appendix
COMPUTER PROGRAMS FOR IDENTIFICA¬
TION, ESTIMATION, AND FORECASTING 222
A.I Program PDQ, 222
A.2 Program ESTIMATE, 223
A.3 Program FORECAST, 224
INDEX, 227
xiv contents
|
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| dewey-search | 338.5/442 |
| dewey-sort | 3338.5 3442 |
| dewey-tens | 330 - Economics |
| discipline | Mathematik Wirtschaftswissenschaften |
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| id | DE-604.BV005543732 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T16:31:25Z |
| institution | BVB |
| isbn | 0816263663 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-003476351 |
| oclc_num | 263541775 |
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| physical | XIV, 231 S. graph. Darst. |
| psigel | TUB-nveb |
| publishDate | 1973 |
| publishDateSearch | 1973 |
| publishDateSort | 1973 |
| publisher | Holden-Day |
| record_format | marc |
| spelling | Nelson, Charles R. Verfasser aut Applied time series analysis for managerial forecasting Oakland, Calif. Holden-Day 1973 XIV, 231 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Análisis de series cronológicas Bedrijfsbeleid gtt Prognoses gtt Prévision commerciale Série chronologique Wiskundige methoden gtt Business forecasting Time-series analysis Zeitreihenanalyse (DE-588)4067486-1 gnd rswk-swf Zeitreihenanalyse (DE-588)4067486-1 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=003476351&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Nelson, Charles R. Applied time series analysis for managerial forecasting Análisis de series cronológicas Bedrijfsbeleid gtt Prognoses gtt Prévision commerciale Série chronologique Wiskundige methoden gtt Business forecasting Time-series analysis Zeitreihenanalyse (DE-588)4067486-1 gnd |
| subject_GND | (DE-588)4067486-1 |
| title | Applied time series analysis for managerial forecasting |
| title_auth | Applied time series analysis for managerial forecasting |
| title_exact_search | Applied time series analysis for managerial forecasting |
| title_full | Applied time series analysis for managerial forecasting |
| title_fullStr | Applied time series analysis for managerial forecasting |
| title_full_unstemmed | Applied time series analysis for managerial forecasting |
| title_short | Applied time series analysis for managerial forecasting |
| title_sort | applied time series analysis for managerial forecasting |
| topic | Análisis de series cronológicas Bedrijfsbeleid gtt Prognoses gtt Prévision commerciale Série chronologique Wiskundige methoden gtt Business forecasting Time-series analysis Zeitreihenanalyse (DE-588)4067486-1 gnd |
| topic_facet | Análisis de series cronológicas Bedrijfsbeleid Prognoses Prévision commerciale Série chronologique Wiskundige methoden Business forecasting Time-series analysis Zeitreihenanalyse |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=003476351&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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