Spatial statistics for data science: theory and practice with R
Spatial data is crucial to improve decision-making in a wide range of fields including environment, health, ecology, urban planning, economy, and society. Spatial Statistics for Data Science: Theory and Practice with R describes statistical methods, modeling approaches, and visualization techniques...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Ration
CRC Press
2024
|
| Ausgabe: | First edition |
| Schriftenreihe: | Chapman and Hall/CRC Data Science Series
|
| Schlagworte: | |
| Zusammenfassung: | Spatial data is crucial to improve decision-making in a wide range of fields including environment, health, ecology, urban planning, economy, and society. Spatial Statistics for Data Science: Theory and Practice with R describes statistical methods, modeling approaches, and visualization techniques to analyze spatial data using R. The book provides a comprehensive overview of the varying types of spatial data, and detailed explanations of the theoretical concepts of spatial statistics, alongside fully reproducible examples which demonstrate how to simulate, describe, and analyze spatial data in various applications. Combining theory and practice, the book includes real-world data science examples such as disease risk mapping, air pollution prediction, species distribution modeling, crime mapping, and real state analyses. The book utilizes publicly available data and offers clear explanations of the R code for importing, manipulating, analyzing, and visualizing data, as well as the interpretation of the results. This ensures contents are easily accessible and fully reproducible for students, researchers, and practitioners. |
| Beschreibung: | xvii, 279 Seiten |
| ISBN: | 9781032633510 9781032641485 |
Internformat
MARC
| LEADER | 00000nam a22000001c 4500 | ||
|---|---|---|---|
| 001 | BV049499689 | ||
| 003 | DE-604 | ||
| 005 | 20240214 | ||
| 007 | t | ||
| 008 | 240115s2024 |||| 00||| eng d | ||
| 020 | |a 9781032633510 |9 978-1-032-63351-0 | ||
| 020 | |a 9781032641485 |c pbk |9 978-1-032-64148-5 | ||
| 035 | |a (OCoLC)1411848014 | ||
| 035 | |a (DE-599)BVBBV049499689 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-703 |a DE-188 |a DE-11 |a DE-20 | ||
| 082 | 0 | |a 001.4/22 | |
| 084 | |a RB 10104 |0 (DE-625)142220:12617 |2 rvk | ||
| 100 | 1 | |a Moraga, Paula |e Verfasser |0 (DE-588)131924484X |4 aut | |
| 245 | 1 | 0 | |a Spatial statistics for data science |b theory and practice with R |
| 250 | |a First edition | ||
| 264 | 1 | |a Boca Ration |b CRC Press |c 2024 | |
| 300 | |a xvii, 279 Seiten | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Chapman and Hall/CRC Data Science Series | |
| 520 | 3 | |a Spatial data is crucial to improve decision-making in a wide range of fields including environment, health, ecology, urban planning, economy, and society. Spatial Statistics for Data Science: Theory and Practice with R describes statistical methods, modeling approaches, and visualization techniques to analyze spatial data using R. The book provides a comprehensive overview of the varying types of spatial data, and detailed explanations of the theoretical concepts of spatial statistics, alongside fully reproducible examples which demonstrate how to simulate, describe, and analyze spatial data in various applications. Combining theory and practice, the book includes real-world data science examples such as disease risk mapping, air pollution prediction, species distribution modeling, crime mapping, and real state analyses. The book utilizes publicly available data and offers clear explanations of the R code for importing, manipulating, analyzing, and visualizing data, as well as the interpretation of the results. This ensures contents are easily accessible and fully reproducible for students, researchers, and practitioners. | |
| 650 | 0 | 7 | |a R |g Programm |0 (DE-588)4705956-4 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Raumdaten |0 (DE-588)4206012-6 |2 gnd |9 rswk-swf |
| 653 | |a Raumbezogene Statistik | ||
| 689 | 0 | 0 | |a Raumdaten |0 (DE-588)4206012-6 |D s |
| 689 | 0 | 1 | |a R |g Programm |0 (DE-588)4705956-4 |D s |
| 689 | 0 | |5 DE-604 | |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-1-032-64152-2 |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-034844846 | |
Datensatz im Suchindex
| _version_ | 1808678414954004480 |
|---|---|
| adam_text | |
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Moraga, Paula |
| author_GND | (DE-588)131924484X |
| author_facet | Moraga, Paula |
| author_role | aut |
| author_sort | Moraga, Paula |
| author_variant | p m pm |
| building | Verbundindex |
| bvnumber | BV049499689 |
| classification_rvk | RB 10104 |
| ctrlnum | (OCoLC)1411848014 (DE-599)BVBBV049499689 |
| dewey-full | 001.4/22 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 001 - Knowledge |
| dewey-raw | 001.4/22 |
| dewey-search | 001.4/22 |
| dewey-sort | 11.4 222 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Allgemeines Geographie |
| discipline_str_mv | Allgemeines Geographie |
| edition | First edition |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a22000001c 4500</leader><controlfield tag="001">BV049499689</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20240214</controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">240115s2024 |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781032633510</subfield><subfield code="9">978-1-032-63351-0</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781032641485</subfield><subfield code="c">pbk</subfield><subfield code="9">978-1-032-64148-5</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1411848014</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV049499689</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-703</subfield><subfield code="a">DE-188</subfield><subfield code="a">DE-11</subfield><subfield code="a">DE-20</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">001.4/22</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">RB 10104</subfield><subfield code="0">(DE-625)142220:12617</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Moraga, Paula</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)131924484X</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Spatial statistics for data science</subfield><subfield code="b">theory and practice with R</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">First edition</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Boca Ration</subfield><subfield code="b">CRC Press</subfield><subfield code="c">2024</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">xvii, 279 Seiten</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">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Chapman and Hall/CRC Data Science Series</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">Spatial data is crucial to improve decision-making in a wide range of fields including environment, health, ecology, urban planning, economy, and society. Spatial Statistics for Data Science: Theory and Practice with R describes statistical methods, modeling approaches, and visualization techniques to analyze spatial data using R. The book provides a comprehensive overview of the varying types of spatial data, and detailed explanations of the theoretical concepts of spatial statistics, alongside fully reproducible examples which demonstrate how to simulate, describe, and analyze spatial data in various applications. Combining theory and practice, the book includes real-world data science examples such as disease risk mapping, air pollution prediction, species distribution modeling, crime mapping, and real state analyses. The book utilizes publicly available data and offers clear explanations of the R code for importing, manipulating, analyzing, and visualizing data, as well as the interpretation of the results. This ensures contents are easily accessible and fully reproducible for students, researchers, and practitioners.</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">R</subfield><subfield code="g">Programm</subfield><subfield code="0">(DE-588)4705956-4</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Raumdaten</subfield><subfield code="0">(DE-588)4206012-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Raumbezogene Statistik</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Raumdaten</subfield><subfield code="0">(DE-588)4206012-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">R</subfield><subfield code="g">Programm</subfield><subfield code="0">(DE-588)4705956-4</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Online-Ausgabe</subfield><subfield code="z">978-1-032-64152-2</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034844846</subfield></datafield></record></collection> |
| id | DE-604.BV049499689 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T23:21:06Z |
| indexdate | 2024-08-29T00:09:10Z |
| institution | BVB |
| isbn | 9781032633510 9781032641485 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034844846 |
| oclc_num | 1411848014 |
| open_access_boolean | |
| owner | DE-703 DE-188 DE-11 DE-20 |
| owner_facet | DE-703 DE-188 DE-11 DE-20 |
| physical | xvii, 279 Seiten |
| publishDate | 2024 |
| publishDateSearch | 2024 |
| publishDateSort | 2024 |
| publisher | CRC Press |
| record_format | marc |
| series2 | Chapman and Hall/CRC Data Science Series |
| spelling | Moraga, Paula Verfasser (DE-588)131924484X aut Spatial statistics for data science theory and practice with R First edition Boca Ration CRC Press 2024 xvii, 279 Seiten txt rdacontent n rdamedia nc rdacarrier Chapman and Hall/CRC Data Science Series Spatial data is crucial to improve decision-making in a wide range of fields including environment, health, ecology, urban planning, economy, and society. Spatial Statistics for Data Science: Theory and Practice with R describes statistical methods, modeling approaches, and visualization techniques to analyze spatial data using R. The book provides a comprehensive overview of the varying types of spatial data, and detailed explanations of the theoretical concepts of spatial statistics, alongside fully reproducible examples which demonstrate how to simulate, describe, and analyze spatial data in various applications. Combining theory and practice, the book includes real-world data science examples such as disease risk mapping, air pollution prediction, species distribution modeling, crime mapping, and real state analyses. The book utilizes publicly available data and offers clear explanations of the R code for importing, manipulating, analyzing, and visualizing data, as well as the interpretation of the results. This ensures contents are easily accessible and fully reproducible for students, researchers, and practitioners. R Programm (DE-588)4705956-4 gnd rswk-swf Raumdaten (DE-588)4206012-6 gnd rswk-swf Raumbezogene Statistik Raumdaten (DE-588)4206012-6 s R Programm (DE-588)4705956-4 s DE-604 Erscheint auch als Online-Ausgabe 978-1-032-64152-2 |
| spellingShingle | Moraga, Paula Spatial statistics for data science theory and practice with R R Programm (DE-588)4705956-4 gnd Raumdaten (DE-588)4206012-6 gnd |
| subject_GND | (DE-588)4705956-4 (DE-588)4206012-6 |
| title | Spatial statistics for data science theory and practice with R |
| title_auth | Spatial statistics for data science theory and practice with R |
| title_exact_search | Spatial statistics for data science theory and practice with R |
| title_exact_search_txtP | Spatial statistics for data science theory and practice with R |
| title_full | Spatial statistics for data science theory and practice with R |
| title_fullStr | Spatial statistics for data science theory and practice with R |
| title_full_unstemmed | Spatial statistics for data science theory and practice with R |
| title_short | Spatial statistics for data science |
| title_sort | spatial statistics for data science theory and practice with r |
| title_sub | theory and practice with R |
| topic | R Programm (DE-588)4705956-4 gnd Raumdaten (DE-588)4206012-6 gnd |
| topic_facet | R Programm Raumdaten |
| work_keys_str_mv | AT moragapaula spatialstatisticsfordatasciencetheoryandpracticewithr |