Multivariate methods and forecasting with IBM SPSS Statistics:
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cham
Springer
[2017]
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| Series: | Statistics and Econometrics for Finance
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | xvii, 178 Seiten |
| ISBN: | 9783319564807 |
| ISSN: | 2199-093X |
Staff View
MARC
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| 245 | 1 | 0 | |a Multivariate methods and forecasting with IBM SPSS Statistics |c Abdulkader Aljandali |
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Record in the Search Index
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| adam_text | Contents
Part I Forecasting Models
1 Multivariate Regression......................................... 3
1.1 The Assumptions Underlying Regression........................... 4
1.1.1 Multicollinearity........................................ 4
1.1.2 Homoscedasticity of the Residuals........................ 5
1.1.3 Normality of the Residuals.............................. 8
1.1.4 Independence of the Residuals............................ 8
1.2 Selecting the Regression Equation.............................. 11
1.3 Multivariate Regression in IBM SPSS Statistics................. 12
1.4 The Cochrane-Orcutt Procedure for Tackling
Autocorrelation................................................ 19
2 Other Useful Topics in Regression.................................... 27
2.1 Binary Logistic Regression..................................... 28
2.1.1 The Linear Probability Model (LPM)...................... 28
2.1.2 The Logit Model....................................... 31
2.1.3 Applying the Logit Model................................ 32
2.1.4 The Logistic Model in IBM SPSS Statistics............... 33
2.1.5 A Financial Application of the Logistic Model........... 39
2.2 Multinomial Logistic Regression................................ 40
2.3 Dummy Regression............................................... 40
2.4 Functional Forms of Regression Models . ....................... 47
2.4.1 The Power Model......................................... 49
2.4.2 The Reciprocal Model.................................... 52
2.4.3 The Linear Trend Model.................................. 55
3 The Box-Jenkins Methodology......................................... 59
3.1 The Property of Staţionarity................................... 59
3.1.1 Trend Differencing...................................... 60
3.1.2 Seasonal Differencing................................... 62
ix
x Contents
3.1.3 Homoscedasticity of the Data......................... 63
3.1.4 Producing a Stationary Time Series
in IBM SPSS Statistics.................................. 63
3.2 The ARIMA Model................................................ 66
3.3 Autocorrelation................................................ 67
3.3.1 ACF.................................................. . 67
3.3.2 PACF................................................... 70
3.3.3 Patterns of the ACF and PACF......................... 71
3.3.4 Applying an ARIMA Model................................. 71
3.4 ARIMA Models in IBM SPSS Statistics............................ 74
4 Exponential Smoothing and Naive Models................................ 81
4.1 Exponential Smoothing Models . ................................ 81
4.2 The Naive Models............................................. 88
Part II Multivariate Methods
5 Factor Analysis.................................................... 97
5.1 The Correlation Matrix ....................................... 98
5.2 The Terminology and Logic of Factor Analysis................ 98
5.3 Rotation and the Naming of Factors............................ 102
5.4 Factor Scores in IBM SPSS Statistics.......................... 105
6 Discriminant Analysis............................................... 107
6.1 The Methodology of Discriminant Analysis...................... 107
6.2 Discriminant Analysis in IBM SPSS Statistics.................. 108
6.3 Results of Applying the IBM SPSS Discriminant
Procedure..................................................... 110
7 Multidimension Scaling (MDS).................................... 117
7.1 Types of MDS Model and Rationale of MDS...................... 119
7.2 Methods for Obtaining Proximities............................. 120
7.3 The Basics of MDS in IBM SPSS Statistics:
Flying Mileages .............................................. 121
7.4 An Example of Nonmetric MDS in IBM SPSS Statistics:
Perceptions of Car Models................................... 126
7.5 Methods of Computing Proximities.......................... 127
7.6 Weighted Multidimensional Scaling in IBM
SPSS, INDSCAL................................................ 130
8 Hierchical Log-linear Analysis...................................... 135
8.1 The Logic and Terminology of Log-linear Analysis.............. 135
8.2 IBM SPSS Statistics Commands for the Saturated
Model....................................................... 138
8.3 The Independence Model....................................... 142
8.4 Hierarchical Models.......................................... 144
8.5 Backward Elimination.......................................... 148
Contents xi
Part III Research Methods
9 Testing for Dependence............................................ 153
9.1 Introduction................................................ 153
9.2 Chi-Square in IBM SPSS Statistics........................... 155
10 Testing for Differences Between Groups........................... 159
10.1 Introduction................................................ 159
10.2 Testing for Population Normality and Equal Variances........ 160
10.3 The One-Way Analysis of Variance (ANOVA)................... 162
10.4 The Kruskal-Wallis Test..................................... 164
11 Current and Constant Prices....................................... 167
11.1 HICP and RPI................................................ 167
11.2 Current and Constant Prices................................. 168
References........................................................... 173
Index................................................................. 175
|
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| id | DE-604.BV044559333 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:55:53Z |
| institution | BVB |
| isbn | 9783319564807 |
| issn | 2199-093X |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029957987 |
| oclc_num | 1002917144 |
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| owner_facet | DE-355 DE-BY-UBR DE-521 DE-83 |
| physical | xvii, 178 Seiten |
| publishDate | 2017 |
| publishDateSearch | 2017 |
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| publisher | Springer |
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| series2 | Statistics and Econometrics for Finance |
| spelling | Aljandali, Abdulkader Verfasser (DE-588)1139004050 aut Multivariate methods and forecasting with IBM SPSS Statistics Abdulkader Aljandali Cham Springer [2017] xvii, 178 Seiten txt rdacontent n rdamedia nc rdacarrier Statistics and Econometrics for Finance 2199-093X Statistics Business enterprises / Finance Big data Economics, Mathematical Statistics for Business/Economics/Mathematical Finance/Insurance Statistical Theory and Methods Big Data/Analytics Business Finance Quantitative Finance Statistik Unternehmen Erscheint auch als Online-Ausgabe 978-3-319-56481-4 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029957987&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Aljandali, Abdulkader Multivariate methods and forecasting with IBM SPSS Statistics Statistics Business enterprises / Finance Big data Economics, Mathematical Statistics for Business/Economics/Mathematical Finance/Insurance Statistical Theory and Methods Big Data/Analytics Business Finance Quantitative Finance Statistik Unternehmen |
| title | Multivariate methods and forecasting with IBM SPSS Statistics |
| title_auth | Multivariate methods and forecasting with IBM SPSS Statistics |
| title_exact_search | Multivariate methods and forecasting with IBM SPSS Statistics |
| title_full | Multivariate methods and forecasting with IBM SPSS Statistics Abdulkader Aljandali |
| title_fullStr | Multivariate methods and forecasting with IBM SPSS Statistics Abdulkader Aljandali |
| title_full_unstemmed | Multivariate methods and forecasting with IBM SPSS Statistics Abdulkader Aljandali |
| title_short | Multivariate methods and forecasting with IBM SPSS Statistics |
| title_sort | multivariate methods and forecasting with ibm spss statistics |
| topic | Statistics Business enterprises / Finance Big data Economics, Mathematical Statistics for Business/Economics/Mathematical Finance/Insurance Statistical Theory and Methods Big Data/Analytics Business Finance Quantitative Finance Statistik Unternehmen |
| topic_facet | Statistics Business enterprises / Finance Big data Economics, Mathematical Statistics for Business/Economics/Mathematical Finance/Insurance Statistical Theory and Methods Big Data/Analytics Business Finance Quantitative Finance Statistik Unternehmen |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029957987&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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