Monte Carlo Method for Partial Differential Equations View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2014

AUTHORS

Alexander Sipin

ABSTRACT

Mean value theorems often use to construct statistical unbiased estimators for the solutions of boundary value problems for PDEs. Every such theorem determines integral equation for PDE’s solution in the space of bounded function in some compact set. The norm of integral operator is one in case of first boundary condition. We formulate the conditions suffice to apply von-Neumann–Ulam scheme for this equation. It is shown that conditions are fulfilled for well-known statistical algorithms for PDEs. More... »

PAGES

465-473

References to SciGraph publications

Book

TITLE

Topics in Statistical Simulation

ISBN

978-1-4939-2103-4
978-1-4939-2104-1

From Grant

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4939-2104-1_46

DOI

http://dx.doi.org/10.1007/978-1-4939-2104-1_46

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1012572118


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": "Vologda State Pedagogical University", 
          "id": "https://www.grid.ac/institutes/grid.445062.1", 
          "name": [
            "Vologda State Pedagogical University, S.Orlov 6, Vologda, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sipin", 
        "givenName": "Alexander", 
        "id": "sg:person.010524252317.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010524252317.52"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1045593618", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-94-009-2243-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045593618", 
          "https://doi.org/10.1007/978-94-009-2243-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-94-009-2243-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045593618", 
          "https://doi.org/10.1007/978-94-009-2243-3"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2014", 
    "datePublishedReg": "2014-01-01", 
    "description": "Mean value theorems often use to construct statistical unbiased estimators for the solutions of boundary value problems for PDEs. Every such theorem determines integral equation for PDE\u2019s solution in the space of bounded function in some compact set. The norm of integral operator is one in case of first boundary condition. We formulate the conditions suffice to apply von-Neumann\u2013Ulam scheme for this equation. It is shown that conditions are fulfilled for well-known statistical algorithms for PDEs.", 
    "editor": [
      {
        "familyName": "Melas", 
        "givenName": "V.B.", 
        "type": "Person"
      }, 
      {
        "familyName": "Mignani", 
        "givenName": "Stefania", 
        "type": "Person"
      }, 
      {
        "familyName": "Monari", 
        "givenName": "Paola", 
        "type": "Person"
      }, 
      {
        "familyName": "Salmaso", 
        "givenName": "Luigi", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-1-4939-2104-1_46", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.6755540", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": {
      "isbn": [
        "978-1-4939-2103-4", 
        "978-1-4939-2104-1"
      ], 
      "name": "Topics in Statistical Simulation", 
      "type": "Book"
    }, 
    "name": "Monte Carlo Method for Partial Differential Equations", 
    "pagination": "465-473", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-1-4939-2104-1_46"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "3be55c5799e72d5db36f620edc055c690f5bda9dd4eb5cbb68f5e0129324c219"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1012572118"
        ]
      }
    ], 
    "publisher": {
      "location": "New York, NY", 
      "name": "Springer New York", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-1-4939-2104-1_46", 
      "https://app.dimensions.ai/details/publication/pub.1012572118"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T14:23", 
    "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_8669_00000250.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-1-4939-2104-1_46"
  }
]
 

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.10.1007/978-1-4939-2104-1_46'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-1-4939-2104-1_46'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-1-4939-2104-1_46'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-1-4939-2104-1_46'


 

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

88 TRIPLES      23 PREDICATES      29 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-1-4939-2104-1_46 schema:about anzsrc-for:01
2 anzsrc-for:0104
3 schema:author N78ab8e0217da4b76bb06a07eabbe48bb
4 schema:citation sg:pub.10.1007/978-94-009-2243-3
5 https://app.dimensions.ai/details/publication/pub.1045593618
6 schema:datePublished 2014
7 schema:datePublishedReg 2014-01-01
8 schema:description Mean value theorems often use to construct statistical unbiased estimators for the solutions of boundary value problems for PDEs. Every such theorem determines integral equation for PDE’s solution in the space of bounded function in some compact set. The norm of integral operator is one in case of first boundary condition. We formulate the conditions suffice to apply von-Neumann–Ulam scheme for this equation. It is shown that conditions are fulfilled for well-known statistical algorithms for PDEs.
9 schema:editor Nee3bd1c7cc97488d9994f50bb4edd10b
10 schema:genre chapter
11 schema:inLanguage en
12 schema:isAccessibleForFree false
13 schema:isPartOf Naafb6b42d8fb47d693c723a40e259ccc
14 schema:name Monte Carlo Method for Partial Differential Equations
15 schema:pagination 465-473
16 schema:productId N8f19d9d6c3e444998d11219c58b50c10
17 Nc1b68c062d5a41b5a4f7956dc96fc506
18 Nfaad024bffe14ca0805cd66799160ef0
19 schema:publisher N789193e4a265430baf12d5d67bee096c
20 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012572118
21 https://doi.org/10.1007/978-1-4939-2104-1_46
22 schema:sdDatePublished 2019-04-15T14:23
23 schema:sdLicense https://scigraph.springernature.com/explorer/license/
24 schema:sdPublisher N558ed6462e7946f59fb45cbed22a58b0
25 schema:url http://link.springer.com/10.1007/978-1-4939-2104-1_46
26 sgo:license sg:explorer/license/
27 sgo:sdDataset chapters
28 rdf:type schema:Chapter
29 N42af60d52ce341b0b7e1cc520566d17d rdf:first N7382803082734a198bc464a149384181
30 rdf:rest Ne3ae3e22334d45a3a8c110d750393bd0
31 N558ed6462e7946f59fb45cbed22a58b0 schema:name Springer Nature - SN SciGraph project
32 rdf:type schema:Organization
33 N7382803082734a198bc464a149384181 schema:familyName Monari
34 schema:givenName Paola
35 rdf:type schema:Person
36 N789193e4a265430baf12d5d67bee096c schema:location New York, NY
37 schema:name Springer New York
38 rdf:type schema:Organisation
39 N78ab8e0217da4b76bb06a07eabbe48bb rdf:first sg:person.010524252317.52
40 rdf:rest rdf:nil
41 N8f19d9d6c3e444998d11219c58b50c10 schema:name readcube_id
42 schema:value 3be55c5799e72d5db36f620edc055c690f5bda9dd4eb5cbb68f5e0129324c219
43 rdf:type schema:PropertyValue
44 N9e2c61502d3c45769f8246f9d087d099 schema:familyName Melas
45 schema:givenName V.B.
46 rdf:type schema:Person
47 Naafb6b42d8fb47d693c723a40e259ccc schema:isbn 978-1-4939-2103-4
48 978-1-4939-2104-1
49 schema:name Topics in Statistical Simulation
50 rdf:type schema:Book
51 Nb26ca41ac11e4ffa898e8b93b18017d4 schema:familyName Mignani
52 schema:givenName Stefania
53 rdf:type schema:Person
54 Nc1b68c062d5a41b5a4f7956dc96fc506 schema:name doi
55 schema:value 10.1007/978-1-4939-2104-1_46
56 rdf:type schema:PropertyValue
57 Ne1e05a7bda394ccfb6d473c22243ae60 rdf:first Nb26ca41ac11e4ffa898e8b93b18017d4
58 rdf:rest N42af60d52ce341b0b7e1cc520566d17d
59 Ne3ae3e22334d45a3a8c110d750393bd0 rdf:first Neb8ee4d1e576490dbf708d8567553860
60 rdf:rest rdf:nil
61 Neb8ee4d1e576490dbf708d8567553860 schema:familyName Salmaso
62 schema:givenName Luigi
63 rdf:type schema:Person
64 Nee3bd1c7cc97488d9994f50bb4edd10b rdf:first N9e2c61502d3c45769f8246f9d087d099
65 rdf:rest Ne1e05a7bda394ccfb6d473c22243ae60
66 Nfaad024bffe14ca0805cd66799160ef0 schema:name dimensions_id
67 schema:value pub.1012572118
68 rdf:type schema:PropertyValue
69 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
70 schema:name Mathematical Sciences
71 rdf:type schema:DefinedTerm
72 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
73 schema:name Statistics
74 rdf:type schema:DefinedTerm
75 sg:grant.6755540 http://pending.schema.org/fundedItem sg:pub.10.1007/978-1-4939-2104-1_46
76 rdf:type schema:MonetaryGrant
77 sg:person.010524252317.52 schema:affiliation https://www.grid.ac/institutes/grid.445062.1
78 schema:familyName Sipin
79 schema:givenName Alexander
80 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010524252317.52
81 rdf:type schema:Person
82 sg:pub.10.1007/978-94-009-2243-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045593618
83 https://doi.org/10.1007/978-94-009-2243-3
84 rdf:type schema:CreativeWork
85 https://app.dimensions.ai/details/publication/pub.1045593618 schema:CreativeWork
86 https://www.grid.ac/institutes/grid.445062.1 schema:alternateName Vologda State Pedagogical University
87 schema:name Vologda State Pedagogical University, S.Orlov 6, Vologda, Russia
88 rdf:type schema:Organization
 




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


...