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County Business Patterns, 1990 [United States]: U.S. Summary, State, and County Data;;Archival Version
- 负责人：
- 关键词：
- DOI：
- doi:10.3886/icpsr06030
- 摘要：
- ng steps for this data collection: Standardized missing values..;;Datasets: DS0: Study-Level Files DS1: United States Summary Data DS2: State Summary Data DS3: County Summary
County Business Patterns, 1989 [United States]: U.S. Summary, State, and County Data;;Archival Version
- 负责人：
- 关键词：
- DOI：
- doi:10.3886/icpsr09740
- 摘要：
- ng steps for this data collection: Standardized missing values..;;Datasets: DS0: Study-Level Files DS1: United States Summary Data DS2: State Summary Data DS3: County Summary
County Business Patterns, 1989 [United States]: U.S. Summary, State, and County Data;;Version 1
- 负责人：
- 关键词：
- DOI：
- doi:10.3886/icpsr09740.v1
- 摘要：
- ng steps for this data collection: Standardized missing values..;;Datasets: DS0: Study-Level Files DS1: United States Summary Data DS2: State Summary Data DS3: County Summary
County Business Patterns, 1988 [United States]: U.S. Summary, State, and County Data;;Version 1
- 负责人：
- 关键词：
- DOI：
- doi:10.3886/icpsr09711.v1
- 摘要：
- ng steps for this data collection: Standardized missing values..;;Datasets: DS0: Study-Level Files DS1: 1988 File 1B (United States Summary Data) DS2: 1988 File 1B (State Summary
Data from: Estimation of individual growth trajectories when repeated measures are missing
- 负责人：
- DOI：
- doi:10.5061/dryad.r6j80
- 摘要：
- to estimate growth in data from wild populations with missing observations and observation error. Previous work has shown that linear mixed models (LMMs
Data from: Quantifying the relative effects of environmental and direct transmission of norovirus
- 负责人：
- DOI：
- doi:10.5061/dryad.mb79n
- 摘要：
- not been quantified. Objective: We employ a novel mathematical model of norovirus transmission, and fit the model to daily incidence data from a major norovirus
Data from: Bayesian hierarchical models for spatially misaligned data in R
- 负责人：
- 关键词：
- DOI：
- doi:10.5061/dryad.3g9s2
- 摘要：
- Spatial misalignment occurs when at least one of multiple outcome variables is missing at an observed location. For spatial data, prediction of these
Data from: A new family of dissimilarity metrics for discrete character matrices that include inapplicable characters and its importa
- 负责人：
- 关键词：
- phylogenetic analysis;disparity;character data;Macroevolution;dissimilarity;Gower's coefficient
- DOI：
- doi:10.5061/dryad.r3k7m3c
- 摘要：
- tuations, it is common practice to treat inapplicable characters as missing data when calculating dissimilarity matrices for disparity studies. For commonly use
Data from: Correcting for missing and irregular data in home-range estimation
- 负责人：
- University Of Konstanz
- 关键词：
- animal movement animal tracking autocorrelation home range Indonesia irregular sampling kernel density estimation Komodo National Park Manta Manta alfredi
- DOI：
- doi:10.5441/001/1.3gj67c2k
- 摘要：
- ) Correcting for missing and irregular data in home-range estimation. Ecological Applications. doi:10.1002/eap.1704;;Home-range estimation is an importa
Data from: PHYLACINE 1.2: The Phylogenetic Atlas of Mammal Macroecology
- 负责人：
- DOI：
- doi:10.5061/dryad.bp26v20
- 摘要：
- of missing data. Furthermore, most available data sets ignore the large impact that humans have had on species ranges and diversity. Ignoring these impacts can lead
