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1 to 10 of 1,065 Results
00_Readme.txt
Apr 10, 2026 - Replication Data for: Leap, Hare, Leap! Long-distance dispersal in mountain hare revealed by GPS collaring
Plain Text - 2.4 KB - MD5: c11023a002a9a4fd5dab3fb327db3895
Data_Pedersen_et_al_2026.csv
Apr 10, 2026 - Replication Data for: Leap, Hare, Leap! Long-distance dispersal in mountain hare revealed by GPS collaring
Comma Separated Values - 243.3 KB - MD5: 566f0bde9003da169389331e96fa9ca7
Position data of hare 706
00_README.txt
Mar 25, 2026 - Simulated data sets for: seqwrap: an R package for flexible iterative fitting of high-dimensional data
Plain Text - 5.3 KB - MD5: 45b711f581c7c1255906694020427d97
m1_estimates_1.RDS
Mar 25, 2026 - Simulated data sets for: seqwrap: an R package for flexible iterative fitting of high-dimensional data
Unknown - 4.4 MB - MD5: ccfc5648379a12331d70d4db737a5551
This file contains model estimates from a specific model and data set, which are stored in `data_sim/estimates` and `data_sim/estimates2`. The naming convention follows `[model]_estimates_[dataset].RDS`, where model refers to a specific model specification, and dataset refers to a data set within a dispersion scenario.
m1_estimates_10.RDS
Mar 25, 2026 - Simulated data sets for: seqwrap: an R package for flexible iterative fitting of high-dimensional data
Unknown - 4.4 MB - MD5: 1a54cbae199a32e7cf0cdaa5fb3750a5
This file contains model estimates from a specific model and data set, which are stored in `data_sim/estimates` and `data_sim/estimates2`. The naming convention follows `[model]_estimates_[dataset].RDS`, where model refers to a specific model specification, and dataset refers to a data set within a dispersion scenario.
m1_estimates_2.RDS
Mar 25, 2026 - Simulated data sets for: seqwrap: an R package for flexible iterative fitting of high-dimensional data
Unknown - 4.3 MB - MD5: 62101cb0fd16e44dcac8d0aca74d82d0
This file contains model estimates from a specific model and data set, which are stored in `data_sim/estimates` and `data_sim/estimates2`. The naming convention follows `[model]_estimates_[dataset].RDS`, where model refers to a specific model specification, and dataset refers to a data set within a dispersion scenario.
m1_estimates_3.RDS
Mar 25, 2026 - Simulated data sets for: seqwrap: an R package for flexible iterative fitting of high-dimensional data
Unknown - 4.4 MB - MD5: f6a8045a054436c9753480d8c234aac7
This file contains model estimates from a specific model and data set, which are stored in `data_sim/estimates` and `data_sim/estimates2`. The naming convention follows `[model]_estimates_[dataset].RDS`, where model refers to a specific model specification, and dataset refers to a data set within a dispersion scenario.
m1_estimates_4.RDS
Mar 25, 2026 - Simulated data sets for: seqwrap: an R package for flexible iterative fitting of high-dimensional data
Unknown - 4.4 MB - MD5: 80eb899fe3c097609edd7d0d0c1e8e04
This file contains model estimates from a specific model and data set, which are stored in `data_sim/estimates` and `data_sim/estimates2`. The naming convention follows `[model]_estimates_[dataset].RDS`, where model refers to a specific model specification, and dataset refers to a data set within a dispersion scenario.
m1_estimates_5.RDS
Mar 25, 2026 - Simulated data sets for: seqwrap: an R package for flexible iterative fitting of high-dimensional data
Unknown - 4.4 MB - MD5: c45ee98dd0b8b0cf0d5a4b3bc04e7fac
This file contains model estimates from a specific model and data set, which are stored in `data_sim/estimates` and `data_sim/estimates2`. The naming convention follows `[model]_estimates_[dataset].RDS`, where model refers to a specific model specification, and dataset refers to a data set within a dispersion scenario.
m1_estimates_6.RDS
Mar 25, 2026 - Simulated data sets for: seqwrap: an R package for flexible iterative fitting of high-dimensional data
Unknown - 4.4 MB - MD5: 6b2d51136c9b1950b004b0e1d29d8b93
This file contains model estimates from a specific model and data set, which are stored in `data_sim/estimates` and `data_sim/estimates2`. The naming convention follows `[model]_estimates_[dataset].RDS`, where model refers to a specific model specification, and dataset refers to a data set within a dispersion scenario.
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