Fundamentals of High-Dimensional Statistics: With Exercises and R Labs
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer International Publishing
2022
Cham Springer |
| Ausgabe: | 1st ed. 2022 |
| Schriftenreihe: | Springer Texts in Statistics
|
| Schlagworte: | |
| Online-Zugang: | BTU01 FAB01 FHN01 FHR01 FKE01 HTW01 TUM01 UBM01 UBT01 UBW01 UBY01 UEI01 UPA01 URL des Erstveröffentlichers |
| Beschreibung: | 1 Online-Ressource (XIV, 355 p. 34 illus., 21 illus. in color) |
| ISBN: | 9783030737924 |
| ISSN: | 2197-4136 |
| DOI: | 10.1007/978-3-030-73792-4 |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV047635566 | ||
| 003 | DE-604 | ||
| 005 | 20240304 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 211213s2022 |||| o||u| ||||||eng d | ||
| 020 | |a 9783030737924 |c Online |9 978-3-030-73792-4 | ||
| 024 | 7 | |a 10.1007/978-3-030-73792-4 |2 doi | |
| 035 | |a (ZDB-2-SMA)9783030737924 | ||
| 035 | |a (OCoLC)1289759191 | ||
| 035 | |a (DE-599)BVBBV047635566 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-824 |a DE-19 |a DE-1043 |a DE-523 |a DE-703 |a DE-188 |a DE-859 |a DE-91 |a DE-634 |a DE-898 |a DE-706 |a DE-739 |a DE-20 |a DE-92 | ||
| 082 | 0 | |a 519.5 |2 23 | |
| 084 | |a SK 850 |0 (DE-625)143263: |2 rvk | ||
| 084 | |a QH 230 |0 (DE-625)141545: |2 rvk | ||
| 100 | 1 | |a Lederer, Johannes |d 1984- |e Verfasser |0 (DE-588)1055925775 |4 aut | |
| 245 | 1 | 0 | |a Fundamentals of High-Dimensional Statistics |b With Exercises and R Labs |c by Johannes Lederer |
| 250 | |a 1st ed. 2022 | ||
| 264 | 1 | |a Cham |b Springer International Publishing |c 2022 | |
| 264 | 1 | |a Cham |b Springer | |
| 300 | |a 1 Online-Ressource (XIV, 355 p. 34 illus., 21 illus. in color) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Springer Texts in Statistics |x 2197-4136 | |
| 650 | 4 | |a Statistical Theory and Methods | |
| 650 | 4 | |a Big Data | |
| 650 | 4 | |a Data Structures and Information Theory | |
| 650 | 4 | |a Artificial Intelligence | |
| 650 | 4 | |a Statistics and Computing/Statistics Programs | |
| 650 | 4 | |a Machine Learning | |
| 650 | 4 | |a Statistics | |
| 650 | 4 | |a Big data | |
| 650 | 4 | |a Data structures (Computer science) | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Machine learning | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-3-030-73791-7 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-3-030-73793-1 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-3-030-73794-8 |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-030-73792-4 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-2-SMA | ||
| 940 | 1 | |q ZDB-2-SMA_2022 | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-033019861 | ||
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l BTU01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l FAB01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l FHN01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l FHR01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l FKE01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l HTW01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l TUM01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l UBM01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l UBT01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l UBW01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l UBY01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l UEI01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-3-030-73792-4 |l UPA01 |p ZDB-2-SMA |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804183084445204480 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Lederer, Johannes 1984- |
| author_GND | (DE-588)1055925775 |
| author_facet | Lederer, Johannes 1984- |
| author_role | aut |
| author_sort | Lederer, Johannes 1984- |
| author_variant | j l jl |
| building | Verbundindex |
| bvnumber | BV047635566 |
| classification_rvk | SK 850 QH 230 |
| collection | ZDB-2-SMA |
| ctrlnum | (ZDB-2-SMA)9783030737924 (OCoLC)1289759191 (DE-599)BVBBV047635566 |
| dewey-full | 519.5 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5 |
| dewey-search | 519.5 |
| dewey-sort | 3519.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Mathematik Wirtschaftswissenschaften |
| doi_str_mv | 10.1007/978-3-030-73792-4 |
| edition | 1st ed. 2022 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03307nmm a2200709zc 4500</leader><controlfield tag="001">BV047635566</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20240304 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">211213s2022 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783030737924</subfield><subfield code="c">Online</subfield><subfield code="9">978-3-030-73792-4</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-3-030-73792-4</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-2-SMA)9783030737924</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1289759191</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047635566</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-824</subfield><subfield code="a">DE-19</subfield><subfield code="a">DE-1043</subfield><subfield code="a">DE-523</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-188</subfield><subfield code="a">DE-859</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-634</subfield><subfield code="a">DE-898</subfield><subfield code="a">DE-706</subfield><subfield code="a">DE-739</subfield><subfield code="a">DE-20</subfield><subfield code="a">DE-92</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">519.5</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">SK 850</subfield><subfield code="0">(DE-625)143263:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">QH 230</subfield><subfield code="0">(DE-625)141545:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Lederer, Johannes</subfield><subfield code="d">1984-</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1055925775</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Fundamentals of High-Dimensional Statistics</subfield><subfield code="b">With Exercises and R Labs</subfield><subfield code="c">by Johannes Lederer</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st ed. 2022</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cham</subfield><subfield code="b">Springer International Publishing</subfield><subfield code="c">2022</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cham</subfield><subfield code="b">Springer</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (XIV, 355 p. 34 illus., 21 illus. in color)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Springer Texts in Statistics</subfield><subfield code="x">2197-4136</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistical Theory and Methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Big Data</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data Structures and Information Theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial Intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistics and Computing/Statistics Programs</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine Learning</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistics </subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Big data</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data structures (Computer science)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine learning</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-3-030-73791-7</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-3-030-73793-1</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-3-030-73794-8</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SMA</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-SMA_2022</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-033019861</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">BTU01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">FAB01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">FHN01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">FHR01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">FKE01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">HTW01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">TUM01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">UBM01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">UBT01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">UBW01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">UBY01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">UEI01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-73792-4</subfield><subfield code="l">UPA01</subfield><subfield code="p">ZDB-2-SMA</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV047635566 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T18:46:38Z |
| indexdate | 2024-07-10T09:17:49Z |
| institution | BVB |
| isbn | 9783030737924 |
| issn | 2197-4136 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033019861 |
| oclc_num | 1289759191 |
| open_access_boolean | |
| owner | DE-824 DE-19 DE-BY-UBM DE-1043 DE-523 DE-703 DE-188 DE-859 DE-91 DE-BY-TUM DE-634 DE-898 DE-BY-UBR DE-706 DE-739 DE-20 DE-92 |
| owner_facet | DE-824 DE-19 DE-BY-UBM DE-1043 DE-523 DE-703 DE-188 DE-859 DE-91 DE-BY-TUM DE-634 DE-898 DE-BY-UBR DE-706 DE-739 DE-20 DE-92 |
| physical | 1 Online-Ressource (XIV, 355 p. 34 illus., 21 illus. in color) |
| psigel | ZDB-2-SMA ZDB-2-SMA_2022 |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | Springer International Publishing Springer |
| record_format | marc |
| series2 | Springer Texts in Statistics |
| spelling | Lederer, Johannes 1984- Verfasser (DE-588)1055925775 aut Fundamentals of High-Dimensional Statistics With Exercises and R Labs by Johannes Lederer 1st ed. 2022 Cham Springer International Publishing 2022 Cham Springer 1 Online-Ressource (XIV, 355 p. 34 illus., 21 illus. in color) txt rdacontent c rdamedia cr rdacarrier Springer Texts in Statistics 2197-4136 Statistical Theory and Methods Big Data Data Structures and Information Theory Artificial Intelligence Statistics and Computing/Statistics Programs Machine Learning Statistics Big data Data structures (Computer science) Artificial intelligence Machine learning Erscheint auch als Druck-Ausgabe 978-3-030-73791-7 Erscheint auch als Druck-Ausgabe 978-3-030-73793-1 Erscheint auch als Druck-Ausgabe 978-3-030-73794-8 https://doi.org/10.1007/978-3-030-73792-4 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Lederer, Johannes 1984- Fundamentals of High-Dimensional Statistics With Exercises and R Labs Statistical Theory and Methods Big Data Data Structures and Information Theory Artificial Intelligence Statistics and Computing/Statistics Programs Machine Learning Statistics Big data Data structures (Computer science) Artificial intelligence Machine learning |
| title | Fundamentals of High-Dimensional Statistics With Exercises and R Labs |
| title_auth | Fundamentals of High-Dimensional Statistics With Exercises and R Labs |
| title_exact_search | Fundamentals of High-Dimensional Statistics With Exercises and R Labs |
| title_exact_search_txtP | Fundamentals of High-Dimensional Statistics With Exercises and R Labs |
| title_full | Fundamentals of High-Dimensional Statistics With Exercises and R Labs by Johannes Lederer |
| title_fullStr | Fundamentals of High-Dimensional Statistics With Exercises and R Labs by Johannes Lederer |
| title_full_unstemmed | Fundamentals of High-Dimensional Statistics With Exercises and R Labs by Johannes Lederer |
| title_short | Fundamentals of High-Dimensional Statistics |
| title_sort | fundamentals of high dimensional statistics with exercises and r labs |
| title_sub | With Exercises and R Labs |
| topic | Statistical Theory and Methods Big Data Data Structures and Information Theory Artificial Intelligence Statistics and Computing/Statistics Programs Machine Learning Statistics Big data Data structures (Computer science) Artificial intelligence Machine learning |
| topic_facet | Statistical Theory and Methods Big Data Data Structures and Information Theory Artificial Intelligence Statistics and Computing/Statistics Programs Machine Learning Statistics Big data Data structures (Computer science) Artificial intelligence Machine learning |
| url | https://doi.org/10.1007/978-3-030-73792-4 |
| work_keys_str_mv | AT ledererjohannes fundamentalsofhighdimensionalstatisticswithexercisesandrlabs |