Spline smoothing for experimental data under zero median of the noise View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-06

AUTHORS

P. I. Balk, A. S. Dolgal’

ABSTRACT

We propose an algorithm for computing parameter estimates for a smoothing cubic spline that minimize the estimated expectation of losses. Instead of the usual assumption that the noise is centered we use an assumption which is more realistic for many practical smoothing problems, namely that it is zero median. The problem setting is augmented by prior deterministic information in the form of constraints on linear combinations of parameters of spline functions. We obtain explicit representations of such estimates and give their qualitative interpretation. Based on the results of a numerical experiment, we establish a high degree of robustness of the solutions to the presence of outliers in the measurements, including same sign outliers, and the possibility to fairly reliably determine the actual accuracy of the resulting estimates of spline parameters by the attained minimum risk value. More... »

PAGES

1072-1086

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1134/s000511791706008x

DOI

http://dx.doi.org/10.1134/s000511791706008x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1085937617


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/2008/0102", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Applied Mathematics", 
        "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": {
          "name": [
            "Institute of Applied Geodesics, Berlin, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Balk", 
        "givenName": "P. I.", 
        "id": "sg:person.010317300625.40", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010317300625.40"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Mining Institute of the Ural Branch of the Russian Academy of Sciences", 
          "id": "https://www.grid.ac/institutes/grid.473900.9", 
          "name": [
            "Mining Institute of the Ural Branch of the Russian Academy of Sciences, Perm, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Dolgal\u2019", 
        "givenName": "A. S.", 
        "id": "sg:person.015125670046.20", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015125670046.20"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1003386853", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-662-02772-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003386853", 
          "https://doi.org/10.1007/978-3-662-02772-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-662-02772-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003386853", 
          "https://doi.org/10.1007/978-3-662-02772-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s0005117911050055", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032596718", 
          "https://doi.org/10.1134/s0005117911050055"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2017-06", 
    "datePublishedReg": "2017-06-01", 
    "description": "We propose an algorithm for computing parameter estimates for a smoothing cubic spline that minimize the estimated expectation of losses. Instead of the usual assumption that the noise is centered we use an assumption which is more realistic for many practical smoothing problems, namely that it is zero median. The problem setting is augmented by prior deterministic information in the form of constraints on linear combinations of parameters of spline functions. We obtain explicit representations of such estimates and give their qualitative interpretation. Based on the results of a numerical experiment, we establish a high degree of robustness of the solutions to the presence of outliers in the measurements, including same sign outliers, and the possibility to fairly reliably determine the actual accuracy of the resulting estimates of spline parameters by the attained minimum risk value.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1134/s000511791706008x", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1136242", 
        "issn": [
          "0005-1179", 
          "0005-2310"
        ], 
        "name": "Automation and Remote Control", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "6", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "78"
      }
    ], 
    "name": "Spline smoothing for experimental data under zero median of the noise", 
    "pagination": "1072-1086", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "b6b1a9819500332031cf3c1cbf97d21c4c11db1480aeb3f84fc2b7c944f4e4ec"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1134/s000511791706008x"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1085937617"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1134/s000511791706008x", 
      "https://app.dimensions.ai/details/publication/pub.1085937617"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T14:05", 
    "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_8660_00000493.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1134/S000511791706008X"
  }
]
 

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.10.1134/s000511791706008x'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1134/s000511791706008x'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1134/s000511791706008x'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1134/s000511791706008x'


 

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

80 TRIPLES      21 PREDICATES      30 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1134/s000511791706008x schema:about anzsrc-for:01
2 anzsrc-for:0102
3 schema:author Nc34c9de723d7460ab3a559ee61fe7350
4 schema:citation sg:pub.10.1007/978-3-662-02772-1
5 sg:pub.10.1134/s0005117911050055
6 https://app.dimensions.ai/details/publication/pub.1003386853
7 schema:datePublished 2017-06
8 schema:datePublishedReg 2017-06-01
9 schema:description We propose an algorithm for computing parameter estimates for a smoothing cubic spline that minimize the estimated expectation of losses. Instead of the usual assumption that the noise is centered we use an assumption which is more realistic for many practical smoothing problems, namely that it is zero median. The problem setting is augmented by prior deterministic information in the form of constraints on linear combinations of parameters of spline functions. We obtain explicit representations of such estimates and give their qualitative interpretation. Based on the results of a numerical experiment, we establish a high degree of robustness of the solutions to the presence of outliers in the measurements, including same sign outliers, and the possibility to fairly reliably determine the actual accuracy of the resulting estimates of spline parameters by the attained minimum risk value.
10 schema:genre research_article
11 schema:inLanguage en
12 schema:isAccessibleForFree false
13 schema:isPartOf N4de94365ab1e44559326cfeb467589d6
14 Na7b3b23e04b84858aa4e30d43b15eabd
15 sg:journal.1136242
16 schema:name Spline smoothing for experimental data under zero median of the noise
17 schema:pagination 1072-1086
18 schema:productId N96ab15ce82464cedafe5b638e604353d
19 Nbf59664eb8334cf7a4aa585fc40eed80
20 Nce3a01cdd6884228bffc12e7548a59ca
21 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085937617
22 https://doi.org/10.1134/s000511791706008x
23 schema:sdDatePublished 2019-04-10T14:05
24 schema:sdLicense https://scigraph.springernature.com/explorer/license/
25 schema:sdPublisher N8185bc7ce06845adb28e25eb9ba555b7
26 schema:url http://link.springer.com/10.1134/S000511791706008X
27 sgo:license sg:explorer/license/
28 sgo:sdDataset articles
29 rdf:type schema:ScholarlyArticle
30 N2ee53fc884ab4987ac5d6508bb793d44 rdf:first sg:person.015125670046.20
31 rdf:rest rdf:nil
32 N4de94365ab1e44559326cfeb467589d6 schema:volumeNumber 78
33 rdf:type schema:PublicationVolume
34 N5512d5f52c61444eaee6fe64b9a22311 schema:name Institute of Applied Geodesics, Berlin, Germany
35 rdf:type schema:Organization
36 N8185bc7ce06845adb28e25eb9ba555b7 schema:name Springer Nature - SN SciGraph project
37 rdf:type schema:Organization
38 N96ab15ce82464cedafe5b638e604353d schema:name dimensions_id
39 schema:value pub.1085937617
40 rdf:type schema:PropertyValue
41 Na7b3b23e04b84858aa4e30d43b15eabd schema:issueNumber 6
42 rdf:type schema:PublicationIssue
43 Nbf59664eb8334cf7a4aa585fc40eed80 schema:name readcube_id
44 schema:value b6b1a9819500332031cf3c1cbf97d21c4c11db1480aeb3f84fc2b7c944f4e4ec
45 rdf:type schema:PropertyValue
46 Nc34c9de723d7460ab3a559ee61fe7350 rdf:first sg:person.010317300625.40
47 rdf:rest N2ee53fc884ab4987ac5d6508bb793d44
48 Nce3a01cdd6884228bffc12e7548a59ca schema:name doi
49 schema:value 10.1134/s000511791706008x
50 rdf:type schema:PropertyValue
51 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
52 schema:name Mathematical Sciences
53 rdf:type schema:DefinedTerm
54 anzsrc-for:0102 schema:inDefinedTermSet anzsrc-for:
55 schema:name Applied Mathematics
56 rdf:type schema:DefinedTerm
57 sg:journal.1136242 schema:issn 0005-1179
58 0005-2310
59 schema:name Automation and Remote Control
60 rdf:type schema:Periodical
61 sg:person.010317300625.40 schema:affiliation N5512d5f52c61444eaee6fe64b9a22311
62 schema:familyName Balk
63 schema:givenName P. I.
64 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010317300625.40
65 rdf:type schema:Person
66 sg:person.015125670046.20 schema:affiliation https://www.grid.ac/institutes/grid.473900.9
67 schema:familyName Dolgal’
68 schema:givenName A. S.
69 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015125670046.20
70 rdf:type schema:Person
71 sg:pub.10.1007/978-3-662-02772-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003386853
72 https://doi.org/10.1007/978-3-662-02772-1
73 rdf:type schema:CreativeWork
74 sg:pub.10.1134/s0005117911050055 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032596718
75 https://doi.org/10.1134/s0005117911050055
76 rdf:type schema:CreativeWork
77 https://app.dimensions.ai/details/publication/pub.1003386853 schema:CreativeWork
78 https://www.grid.ac/institutes/grid.473900.9 schema:alternateName Mining Institute of the Ural Branch of the Russian Academy of Sciences
79 schema:name Mining Institute of the Ural Branch of the Russian Academy of Sciences, Perm, Russia
80 rdf:type schema:Organization
 




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


...