Finite mixture and Markov switching models:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New York, NY
Springer
2006
|
| Series: | Springer series in statistics
|
| Subjects: | |
| Online Access: | Inhaltstext Inhaltsverzeichnis |
| Physical Description: | XIX, 492 S. graph. Darst. |
| ISBN: | 0387329099 9780387329093 |
Staff View
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| 100 | 1 | |a Frühwirth-Schnatter, Sylvia |d 1959- |e Verfasser |0 (DE-588)131410105 |4 aut | |
| 245 | 1 | 0 | |a Finite mixture and Markov switching models |c Sylvia Frühwirth-Schnatter |
| 264 | 1 | |a New York, NY |b Springer |c 2006 | |
| 300 | |a XIX, 492 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Springer series in statistics | |
| 650 | 7 | |a Markov-modellen |2 gtt | |
| 650 | 7 | |a Statistische modellen |2 gtt | |
| 650 | 4 | |a Markov processes | |
| 650 | 4 | |a Mixture distributions (Probability theory) | |
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Record in the Search Index
| _version_ | 1817704601149767680 |
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| adam_text |
Contents
1
1.1
1.2
1.2.1
1.2.2
Mixture Distributions
1.2.3
1.2.4
1.2.5
Mixture Distributions
1.3
1.3.1
the Components
1.3.2
1.3.3
1.3.4
2
Known Number of Components
2.1
2.2
2.2.1
2.2.2
2.3
2.3.1
2.3.2
2.3.3
Component Parameters
2.3.4
2.4
2.4.1
X
2.4.2
2.4.3
for Two Examples
2.4.4
2.4.5
2.4.6
2.4.7
3
with Known Number of Components
3.1
3.2
3.2.1
3.2.2
Mixture Posteriors
3.2.3
3.2.4
3.2.5
3.2.6
3.3
3.3.1
3.3.2
Specific Functionals
3.3.3
the Allocations
3.3.4
the Allocations
3.4
3.4.1
3.4.2
3.5
and MCMC
3.5.1
3.5.2
Poisson
3.5.3
General Mixtures
3.5.4
3.5.5
3.5.6
3.6
3.6.1
the Parameters
3.6.2
3.6.3
Contents
3.7
Posterior Draws
3.7.1
Posterior Density
3.7.2
3.7.3
3.7.4
3.7.5
Hierarchical Prior
3.7.6
3.7.7
4
Model Specification Uncertainty
4.1
4.2
Specification Uncertainty
4.2.1
Specification Uncertainty
4.2.2
Overfitting Finite Mixture Models
4.2.3
4.3
of Components
4.3.1
4.3.2
4.3.3
of Moments
4.3.4
4.3.5
4.4
4.4.1
4.4.2
4.4.3
4.5
4.5.1
4.5.2
4.5.3
4.5.4
4.5.5
4.5.6
XII
5
Mixtures Models Under Model Specification Uncertainty
5.1
5.2
5.2.1
5.2.2
5.2.3
5.3
5.3.1
5.3.2
Components
5.3.3
Mixture Models
5.4
Marginal Likelihood
5.4.1
5.4.2
5.4.3
5.4.4
5.4.5
5.4.6
5.4.7
Based Estimators
5.4.8
5.5
Density Ratios
5.5.1
5.5.2
5.5.3
5.6
6
6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.2
6.2.1
Are Known
6.2.2
6.2.3
6.2.4
6.2.5
Contents
6.2.6
the Components
6.2.7
6.2.8
6.3
6.3.1
Are Known
6.3.2
6.3.3
6.3.4
6.4
6.4.1
6.4.2
Data Analysis Based on Finite Mixtures
7.1
7.1.1
7.1.2
Mixture Models
7.1.3
MAP Approach
7.1.4
of Components
7.1.5
7.1.6
7.1.7
7.1.8
7.2
7.2.1
7.2.2
Finite Mixtures
7.2.3
7.2.4
7.3
Student-ŕ
7.3.1
7.3.2
7.4
7.4.1
7.4.2
7.4.3
7.4.4
7.4.5
in Bayesian Analysis
XIV
8
8.1
8.2
8.2.1
8.2.2
8.2.3
Regression Models
8.2.4
8.3
Regression Models
8.3.1
8.3.2
Are Known
8.3.3
8.3.4
Are Unknown
8.3.5
8.3.6
8.4
8.4.1
8.4.2
8.4.3
Are Known
8.4.4
Are Unknown
8.5
8.5.1
8.5.2
8.5.3
8.5.4
Are Known
8.5.5
8.5.6
8.5.7
8.6
8.6.1
of Normals
8.6.2
8.6.3
9
9.1
9.1.1
9.1.2
9.2
Contents
9.2.1
9.2.2
9.2.3
9.2.4
9.3
9.3.1
9.3.2
9.4
9.4.1
9.4.2
Regression Models
9.4.3
9.4.4
9.5
Categorical Data
9.5.1
9.5.2
9.5.3
9.6
9.6.1
9.6.2
10
10.1
10.2
10.2.1
10.2.2
10.2.3
10.2.4
by a Markov Mixture Distribution
10.2.5
Squared Process
10.2.6
Limiting Case
10.2.7
Mixture Distribution
10.3
Distributions
10.3.1
10.3.2
10.3.3
10.3.4
Switching Model
XVI
11
11.1
11.2
11.2.1
11.2.2
11.2.3
11.2.4
11.2.5
11.3
11.3.1
11.3.2
11.3.3
Transition Matrix
11.4
11.4.1
11.4.2
11.4.3
11.4.4
11.5
of States
11.5.1
Mixture Model
11.5.2
Markov Switching Model
11.5.3
and MCMC
11.5.4
11.5.5
11.5.6
Markov Chain
11.5.7
11.5.8
11.6
11.6.1
11.6.2
11.6.3
11.6.4
11.6.5
11.7
of Count Data
11.7.1
11.7.2
Poisson
11.7.3
Contents
12
Switching Models
12.1
12.2
12.2.1
12.2.2
12.2.3
12.2.4
Time Series
12.2.5
12.2.6
GDP Data
12.3
12.3.1
12.3.2
12.4
Switching Models
12.4.1
12.4.2
Sampling-Based Methods
12.5
12.5.1
12.5.2
Markov Switching Models
12.5.3
12.5.4
12.5.5
12.6
12.6.1
12.6.2
Panel Data
12.6.3
Time Series
13
13.1
13.1.1
Without Switching
13.1.2
13.1.3
13.1.4
13.1.5
13.2
Space Models
13.2.1
XVIII
13.2.2
13.2.3
13.2.4
13.2.5
Smoothing Device
13.3
13.3.1
13.3.2
Regression Model
13.3.3
13.3.4
13.3.5
State Space Models
13.4
13.4.1
13.4.2
13.4.3
13.5
13.5.1
13.5.2
Smoother Density
13.5.3
Space Model
13.6
13.6.1
Space Modeling
13.6.2
Nonnormal
13.7
A Appendix
A.I Summary of Probability Distributions
A.I.I The Beta Distribution
A.1.2 The Binomial Distribution
A.1.3 The Dirichlet Distribution
A.
A.1.5 The F-Distribution
A.1.6 The Gamma Distribution
A.1.7 The Geometric Distribution
A.
A.1.9 The Negative Binomial Distribution
A.I.
A.I.
A.I.
A.I.
Contents
A.I.
A.2 Software
References
Index |
| adam_txt |
Contents
1
1.1
1.2
1.2.1
1.2.2
Mixture Distributions
1.2.3
1.2.4
1.2.5
Mixture Distributions
1.3
1.3.1
the Components
1.3.2
1.3.3
1.3.4
2
Known Number of Components
2.1
2.2
2.2.1
2.2.2
2.3
2.3.1
2.3.2
2.3.3
Component Parameters
2.3.4
2.4
2.4.1
X
2.4.2
2.4.3
for Two Examples
2.4.4
2.4.5
2.4.6
2.4.7
3
with Known Number of Components
3.1
3.2
3.2.1
3.2.2
Mixture Posteriors
3.2.3
3.2.4
3.2.5
3.2.6
3.3
3.3.1
3.3.2
Specific Functionals
3.3.3
the Allocations
3.3.4
the Allocations
3.4
3.4.1
3.4.2
3.5
and MCMC
3.5.1
3.5.2
Poisson
3.5.3
General Mixtures
3.5.4
3.5.5
3.5.6
3.6
3.6.1
the Parameters
3.6.2
3.6.3
Contents
3.7
Posterior Draws
3.7.1
Posterior Density
3.7.2
3.7.3
3.7.4
3.7.5
Hierarchical Prior
3.7.6
3.7.7
4
Model Specification Uncertainty
4.1
4.2
Specification Uncertainty
4.2.1
Specification Uncertainty
4.2.2
Overfitting Finite Mixture Models
4.2.3
4.3
of Components
4.3.1
4.3.2
4.3.3
of Moments
4.3.4
4.3.5
4.4
4.4.1
4.4.2
4.4.3
4.5
4.5.1
4.5.2
4.5.3
4.5.4
4.5.5
4.5.6
XII
5
Mixtures Models Under Model Specification Uncertainty
5.1
5.2
5.2.1
5.2.2
5.2.3
5.3
5.3.1
5.3.2
Components
5.3.3
Mixture Models
5.4
Marginal Likelihood
5.4.1
5.4.2
5.4.3
5.4.4
5.4.5
5.4.6
5.4.7
Based Estimators
5.4.8
5.5
Density Ratios
5.5.1
5.5.2
5.5.3
5.6
6
6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.2
6.2.1
Are Known
6.2.2
6.2.3
6.2.4
6.2.5
Contents
6.2.6
the Components
6.2.7
6.2.8
6.3
6.3.1
Are Known
6.3.2
6.3.3
6.3.4
6.4
6.4.1
6.4.2
Data Analysis Based on Finite Mixtures
7.1
7.1.1
7.1.2
Mixture Models
7.1.3
MAP Approach
7.1.4
of Components
7.1.5
7.1.6
7.1.7
7.1.8
7.2
7.2.1
7.2.2
Finite Mixtures
7.2.3
7.2.4
7.3
Student-ŕ
7.3.1
7.3.2
7.4
7.4.1
7.4.2
7.4.3
7.4.4
7.4.5
in Bayesian Analysis
XIV
8
8.1
8.2
8.2.1
8.2.2
8.2.3
Regression Models
8.2.4
8.3
Regression Models
8.3.1
8.3.2
Are Known
8.3.3
8.3.4
Are Unknown
8.3.5
8.3.6
8.4
8.4.1
8.4.2
8.4.3
Are Known
8.4.4
Are Unknown
8.5
8.5.1
8.5.2
8.5.3
8.5.4
Are Known
8.5.5
8.5.6
8.5.7
8.6
8.6.1
of Normals
8.6.2
8.6.3
9
9.1
9.1.1
9.1.2
9.2
Contents
9.2.1
9.2.2
9.2.3
9.2.4
9.3
9.3.1
9.3.2
9.4
9.4.1
9.4.2
Regression Models
9.4.3
9.4.4
9.5
Categorical Data
9.5.1
9.5.2
9.5.3
9.6
9.6.1
9.6.2
10
10.1
10.2
10.2.1
10.2.2
10.2.3
10.2.4
by a Markov Mixture Distribution
10.2.5
Squared Process
10.2.6
Limiting Case
10.2.7
Mixture Distribution
10.3
Distributions
10.3.1
10.3.2
10.3.3
10.3.4
Switching Model
XVI
11
11.1
11.2
11.2.1
11.2.2
11.2.3
11.2.4
11.2.5
11.3
11.3.1
11.3.2
11.3.3
Transition Matrix
11.4
11.4.1
11.4.2
11.4.3
11.4.4
11.5
of States
11.5.1
Mixture Model
11.5.2
Markov Switching Model
11.5.3
and MCMC
11.5.4
11.5.5
11.5.6
Markov Chain
11.5.7
11.5.8
11.6
11.6.1
11.6.2
11.6.3
11.6.4
11.6.5
11.7
of Count Data
11.7.1
11.7.2
Poisson
11.7.3
Contents
12
Switching Models
12.1
12.2
12.2.1
12.2.2
12.2.3
12.2.4
Time Series
12.2.5
12.2.6
GDP Data
12.3
12.3.1
12.3.2
12.4
Switching Models
12.4.1
12.4.2
Sampling-Based Methods
12.5
12.5.1
12.5.2
Markov Switching Models
12.5.3
12.5.4
12.5.5
12.6
12.6.1
12.6.2
Panel Data
12.6.3
Time Series
13
13.1
13.1.1
Without Switching
13.1.2
13.1.3
13.1.4
13.1.5
13.2
Space Models
13.2.1
XVIII
13.2.2
13.2.3
13.2.4
13.2.5
Smoothing Device
13.3
13.3.1
13.3.2
Regression Model
13.3.3
13.3.4
13.3.5
State Space Models
13.4
13.4.1
13.4.2
13.4.3
13.5
13.5.1
13.5.2
Smoother Density
13.5.3
Space Model
13.6
13.6.1
Space Modeling
13.6.2
Nonnormal
13.7
A Appendix
A.I Summary of Probability Distributions
A.I.I The Beta Distribution
A.1.2 The Binomial Distribution
A.1.3 The Dirichlet Distribution
A.
A.1.5 The F-Distribution
A.1.6 The Gamma Distribution
A.1.7 The Geometric Distribution
A.
A.1.9 The Negative Binomial Distribution
A.I.
A.I.
A.I.
A.I.
Contents
A.I.
A.2 Software
References
Index |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Frühwirth-Schnatter, Sylvia 1959- |
| author_GND | (DE-588)131410105 |
| author_facet | Frühwirth-Schnatter, Sylvia 1959- |
| author_role | aut |
| author_sort | Frühwirth-Schnatter, Sylvia 1959- |
| author_variant | s f s sfs |
| building | Verbundindex |
| bvnumber | BV021695569 |
| callnumber-first | Q - Science |
| callnumber-label | QA274 |
| callnumber-raw | QA274.7 |
| callnumber-search | QA274.7 |
| callnumber-sort | QA 3274.7 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | QH 234 QH 320 SK 820 SK 970 |
| classification_tum | MAT 607f |
| ctrlnum | (OCoLC)254881530 (DE-599)BVBBV021695569 |
| discipline | Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Mathematik Wirtschaftswissenschaften |
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| id | DE-604.BV021695569 |
| illustrated | Illustrated |
| index_date | 2024-07-02T15:15:41Z |
| indexdate | 2024-12-06T15:16:31Z |
| institution | BVB |
| isbn | 0387329099 9780387329093 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-014909582 |
| oclc_num | 254881530 |
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| physical | XIX, 492 S. graph. Darst. |
| publishDate | 2006 |
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| publishDateSort | 2006 |
| publisher | Springer |
| record_format | marc |
| series2 | Springer series in statistics |
| spelling | Frühwirth-Schnatter, Sylvia 1959- Verfasser (DE-588)131410105 aut Finite mixture and Markov switching models Sylvia Frühwirth-Schnatter New York, NY Springer 2006 XIX, 492 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Springer series in statistics Markov-modellen gtt Statistische modellen gtt Markov processes Mixture distributions (Probability theory) Hidden-Markov-Modell (DE-588)4352479-5 gnd rswk-swf Zusammengesetzte Verteilung (DE-588)4191153-2 gnd rswk-swf Zusammengesetzte Verteilung (DE-588)4191153-2 s Hidden-Markov-Modell (DE-588)4352479-5 s DE-604 Erscheint auch als Online-Ausgabe 0-387-35768-8 text/html http://deposit.dnb.de/cgi-bin/dokserv?id=2788988&prov=M&dok_var=1&dok_ext=htm Inhaltstext Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014909582&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Frühwirth-Schnatter, Sylvia 1959- Finite mixture and Markov switching models Markov-modellen gtt Statistische modellen gtt Markov processes Mixture distributions (Probability theory) Hidden-Markov-Modell (DE-588)4352479-5 gnd Zusammengesetzte Verteilung (DE-588)4191153-2 gnd |
| subject_GND | (DE-588)4352479-5 (DE-588)4191153-2 |
| title | Finite mixture and Markov switching models |
| title_auth | Finite mixture and Markov switching models |
| title_exact_search | Finite mixture and Markov switching models |
| title_exact_search_txtP | Finite mixture and Markov switching models |
| title_full | Finite mixture and Markov switching models Sylvia Frühwirth-Schnatter |
| title_fullStr | Finite mixture and Markov switching models Sylvia Frühwirth-Schnatter |
| title_full_unstemmed | Finite mixture and Markov switching models Sylvia Frühwirth-Schnatter |
| title_short | Finite mixture and Markov switching models |
| title_sort | finite mixture and markov switching models |
| topic | Markov-modellen gtt Statistische modellen gtt Markov processes Mixture distributions (Probability theory) Hidden-Markov-Modell (DE-588)4352479-5 gnd Zusammengesetzte Verteilung (DE-588)4191153-2 gnd |
| topic_facet | Markov-modellen Statistische modellen Markov processes Mixture distributions (Probability theory) Hidden-Markov-Modell Zusammengesetzte Verteilung |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=2788988&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014909582&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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