Estimating and Detecting Jumps. Applications to $$D\left[ 0,1\right] $$ D 0 , 1 -Valued Linear Processes View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

Denis Bosq

ABSTRACT

This paper is devoted to the estimation of the intensity and the density of jumps for \(D\left[ 0,1\right] \)-valued random variables and the construction of detectors for constant or random jumps. Limit theorems are obtained in the context of continuous observations or high-frequency data. Applications to jumps for \(D\left[ 0,1\right] \)-valued moving average and autoregressive processes are considered. We also study the special case where there is an infinity of jumps. Thus, our approach is somewhat different from that which consists of studying jumps in semimartingales. More... »

PAGES

41-66

References to SciGraph publications

Book

TITLE

Mathematical Statistics and Limit Theorems

ISBN

978-3-319-12441-4
978-3-319-12442-1

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-12442-1_4

DOI

http://dx.doi.org/10.1007/978-3-319-12442-1_4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1017525741


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Statistics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Laboratoire de Statistique Th\u00e9orique et Appliqu\u00e9e", 
          "id": "https://www.grid.ac/institutes/grid.463964.a", 
          "name": [
            "LSTA, Universit\u00e9 Pierre et Marie Curie - Paris 6, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bosq", 
        "givenName": "Denis", 
        "id": "sg:person.015335055755.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015335055755.62"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1006/jmva.1998.1785", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007103013"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmva.2013.11.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014221017"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.spl.2005.10.035", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017255780"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1034653958", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4419-0320-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034653958", 
          "https://doi.org/10.1007/978-1-4419-0320-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4419-0320-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034653958", 
          "https://doi.org/10.1007/978-1-4419-0320-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-1154-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036575891", 
          "https://doi.org/10.1007/978-1-4612-1154-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-1154-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036575891", 
          "https://doi.org/10.1007/978-1-4612-1154-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-5156-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037170055", 
          "https://doi.org/10.1007/978-1-4612-5156-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-5156-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037170055", 
          "https://doi.org/10.1007/978-1-4612-5156-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-1384-0_30", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037854305", 
          "https://doi.org/10.1007/978-1-4612-1384-0_30"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-1384-0_30", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037854305", 
          "https://doi.org/10.1007/978-1-4612-1384-0_30"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1037887112", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4614-3655-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037887112", 
          "https://doi.org/10.1007/978-1-4614-3655-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4614-3655-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037887112", 
          "https://doi.org/10.1007/978-1-4614-3655-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4757-2539-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038602576", 
          "https://doi.org/10.1007/978-1-4757-2539-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4757-2539-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038602576", 
          "https://doi.org/10.1007/978-1-4757-2539-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00533047", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040729850", 
          "https://doi.org/10.1007/bf00533047"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00533047", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040729850", 
          "https://doi.org/10.1007/bf00533047"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0167-7152(93)90004-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050096246"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-1718-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052093296", 
          "https://doi.org/10.1007/978-1-4612-1718-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-1718-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052093296", 
          "https://doi.org/10.1007/978-1-4612-1718-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/1108005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062864437"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aop/1176995150", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064405150"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4615-8162-8_8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1089724303", 
          "https://doi.org/10.1007/978-1-4615-8162-8_8"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2015", 
    "datePublishedReg": "2015-01-01", 
    "description": "This paper is devoted to the estimation of the intensity and the density of jumps for \\(D\\left[ 0,1\\right] \\)-valued random variables and the construction of detectors for constant or random jumps. Limit theorems are obtained in the context of continuous observations or high-frequency data. Applications to jumps for \\(D\\left[ 0,1\\right] \\)-valued moving average and autoregressive processes are considered. We also study the special case where there is an infinity of jumps. Thus, our approach is somewhat different from that which consists of studying jumps in semimartingales.", 
    "editor": [
      {
        "familyName": "Hallin", 
        "givenName": "Marc", 
        "type": "Person"
      }, 
      {
        "familyName": "Mason", 
        "givenName": "David M.", 
        "type": "Person"
      }, 
      {
        "familyName": "Pfeifer", 
        "givenName": "Dietmar", 
        "type": "Person"
      }, 
      {
        "familyName": "Steinebach", 
        "givenName": "Josef G.", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-319-12442-1_4", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-319-12441-4", 
        "978-3-319-12442-1"
      ], 
      "name": "Mathematical Statistics and Limit Theorems", 
      "type": "Book"
    }, 
    "name": "Estimating and Detecting Jumps. Applications to $$D\\left[ 0,1\\right] $$ D 0 , 1 -Valued Linear Processes", 
    "pagination": "41-66", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-319-12442-1_4"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "537ff1fbcca3201d863ad23355037a323a5afbd37d2c8afd5ea2222ded5f586f"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1017525741"
        ]
      }
    ], 
    "publisher": {
      "location": "Cham", 
      "name": "Springer International Publishing", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-319-12442-1_4", 
      "https://app.dimensions.ai/details/publication/pub.1017525741"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T20:05", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8687_00000254.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-3-319-12442-1_4"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-12442-1_4'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-12442-1_4'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-12442-1_4'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-12442-1_4'


 

This table displays all metadata directly associated to this object as RDF triples.

138 TRIPLES      23 PREDICATES      44 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-319-12442-1_4 schema:about anzsrc-for:01
2 anzsrc-for:0104
3 schema:author Nd8d05d86897b43bab177e9b1f114e0de
4 schema:citation sg:pub.10.1007/978-1-4419-0320-4
5 sg:pub.10.1007/978-1-4612-1154-9
6 sg:pub.10.1007/978-1-4612-1384-0_30
7 sg:pub.10.1007/978-1-4612-1718-3
8 sg:pub.10.1007/978-1-4612-5156-9
9 sg:pub.10.1007/978-1-4614-3655-3
10 sg:pub.10.1007/978-1-4615-8162-8_8
11 sg:pub.10.1007/978-1-4757-2539-1
12 sg:pub.10.1007/bf00533047
13 https://app.dimensions.ai/details/publication/pub.1034653958
14 https://app.dimensions.ai/details/publication/pub.1037887112
15 https://doi.org/10.1006/jmva.1998.1785
16 https://doi.org/10.1016/0167-7152(93)90004-3
17 https://doi.org/10.1016/j.jmva.2013.11.013
18 https://doi.org/10.1016/j.spl.2005.10.035
19 https://doi.org/10.1137/1108005
20 https://doi.org/10.1214/aop/1176995150
21 schema:datePublished 2015
22 schema:datePublishedReg 2015-01-01
23 schema:description This paper is devoted to the estimation of the intensity and the density of jumps for \(D\left[ 0,1\right] \)-valued random variables and the construction of detectors for constant or random jumps. Limit theorems are obtained in the context of continuous observations or high-frequency data. Applications to jumps for \(D\left[ 0,1\right] \)-valued moving average and autoregressive processes are considered. We also study the special case where there is an infinity of jumps. Thus, our approach is somewhat different from that which consists of studying jumps in semimartingales.
24 schema:editor N35154fd117d9406fb1a7adc23aa689c7
25 schema:genre chapter
26 schema:inLanguage en
27 schema:isAccessibleForFree false
28 schema:isPartOf Nb6d7ad22a0064b50bd16f84ae1038b18
29 schema:name Estimating and Detecting Jumps. Applications to $$D\left[ 0,1\right] $$ D 0 , 1 -Valued Linear Processes
30 schema:pagination 41-66
31 schema:productId N1f3e5d3a5dc0457c9efa4b2bf828ccbe
32 Nb233525792434a38b87ce04b14e22df3
33 Nd4ad26f8f5a143ca84ee8b5e4b83d2ef
34 schema:publisher N9eaac30d8c66423c85d9e8c090250be1
35 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017525741
36 https://doi.org/10.1007/978-3-319-12442-1_4
37 schema:sdDatePublished 2019-04-15T20:05
38 schema:sdLicense https://scigraph.springernature.com/explorer/license/
39 schema:sdPublisher N7876971a0034405fbfdd94a516a1af11
40 schema:url http://link.springer.com/10.1007/978-3-319-12442-1_4
41 sgo:license sg:explorer/license/
42 sgo:sdDataset chapters
43 rdf:type schema:Chapter
44 N1dc647c8846b4d0287201fde9cc9c4af schema:familyName Mason
45 schema:givenName David M.
46 rdf:type schema:Person
47 N1f3e5d3a5dc0457c9efa4b2bf828ccbe schema:name dimensions_id
48 schema:value pub.1017525741
49 rdf:type schema:PropertyValue
50 N34f30a7386814f9694c7f0a64b2afb5f rdf:first N79327655632d4e1f9e207b65e900f8da
51 rdf:rest N3a27fb14a02b422c97c5484e76e3bc32
52 N35154fd117d9406fb1a7adc23aa689c7 rdf:first N45fee9e304c841ecbaa69272d95f1842
53 rdf:rest N8683fad14deb468e92b1c55d77616629
54 N3a27fb14a02b422c97c5484e76e3bc32 rdf:first N5eee416af5ac472bb5ee0939ee0cc1e9
55 rdf:rest rdf:nil
56 N45fee9e304c841ecbaa69272d95f1842 schema:familyName Hallin
57 schema:givenName Marc
58 rdf:type schema:Person
59 N5eee416af5ac472bb5ee0939ee0cc1e9 schema:familyName Steinebach
60 schema:givenName Josef G.
61 rdf:type schema:Person
62 N7876971a0034405fbfdd94a516a1af11 schema:name Springer Nature - SN SciGraph project
63 rdf:type schema:Organization
64 N79327655632d4e1f9e207b65e900f8da schema:familyName Pfeifer
65 schema:givenName Dietmar
66 rdf:type schema:Person
67 N8683fad14deb468e92b1c55d77616629 rdf:first N1dc647c8846b4d0287201fde9cc9c4af
68 rdf:rest N34f30a7386814f9694c7f0a64b2afb5f
69 N9eaac30d8c66423c85d9e8c090250be1 schema:location Cham
70 schema:name Springer International Publishing
71 rdf:type schema:Organisation
72 Nb233525792434a38b87ce04b14e22df3 schema:name doi
73 schema:value 10.1007/978-3-319-12442-1_4
74 rdf:type schema:PropertyValue
75 Nb6d7ad22a0064b50bd16f84ae1038b18 schema:isbn 978-3-319-12441-4
76 978-3-319-12442-1
77 schema:name Mathematical Statistics and Limit Theorems
78 rdf:type schema:Book
79 Nd4ad26f8f5a143ca84ee8b5e4b83d2ef schema:name readcube_id
80 schema:value 537ff1fbcca3201d863ad23355037a323a5afbd37d2c8afd5ea2222ded5f586f
81 rdf:type schema:PropertyValue
82 Nd8d05d86897b43bab177e9b1f114e0de rdf:first sg:person.015335055755.62
83 rdf:rest rdf:nil
84 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
85 schema:name Mathematical Sciences
86 rdf:type schema:DefinedTerm
87 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
88 schema:name Statistics
89 rdf:type schema:DefinedTerm
90 sg:person.015335055755.62 schema:affiliation https://www.grid.ac/institutes/grid.463964.a
91 schema:familyName Bosq
92 schema:givenName Denis
93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015335055755.62
94 rdf:type schema:Person
95 sg:pub.10.1007/978-1-4419-0320-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034653958
96 https://doi.org/10.1007/978-1-4419-0320-4
97 rdf:type schema:CreativeWork
98 sg:pub.10.1007/978-1-4612-1154-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036575891
99 https://doi.org/10.1007/978-1-4612-1154-9
100 rdf:type schema:CreativeWork
101 sg:pub.10.1007/978-1-4612-1384-0_30 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037854305
102 https://doi.org/10.1007/978-1-4612-1384-0_30
103 rdf:type schema:CreativeWork
104 sg:pub.10.1007/978-1-4612-1718-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052093296
105 https://doi.org/10.1007/978-1-4612-1718-3
106 rdf:type schema:CreativeWork
107 sg:pub.10.1007/978-1-4612-5156-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037170055
108 https://doi.org/10.1007/978-1-4612-5156-9
109 rdf:type schema:CreativeWork
110 sg:pub.10.1007/978-1-4614-3655-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037887112
111 https://doi.org/10.1007/978-1-4614-3655-3
112 rdf:type schema:CreativeWork
113 sg:pub.10.1007/978-1-4615-8162-8_8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1089724303
114 https://doi.org/10.1007/978-1-4615-8162-8_8
115 rdf:type schema:CreativeWork
116 sg:pub.10.1007/978-1-4757-2539-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038602576
117 https://doi.org/10.1007/978-1-4757-2539-1
118 rdf:type schema:CreativeWork
119 sg:pub.10.1007/bf00533047 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040729850
120 https://doi.org/10.1007/bf00533047
121 rdf:type schema:CreativeWork
122 https://app.dimensions.ai/details/publication/pub.1034653958 schema:CreativeWork
123 https://app.dimensions.ai/details/publication/pub.1037887112 schema:CreativeWork
124 https://doi.org/10.1006/jmva.1998.1785 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007103013
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1016/0167-7152(93)90004-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050096246
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/j.jmva.2013.11.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014221017
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1016/j.spl.2005.10.035 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017255780
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1137/1108005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062864437
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1214/aop/1176995150 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064405150
135 rdf:type schema:CreativeWork
136 https://www.grid.ac/institutes/grid.463964.a schema:alternateName Laboratoire de Statistique Théorique et Appliquée
137 schema:name LSTA, Université Pierre et Marie Curie - Paris 6, Paris, France
138 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...