cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/tectsl/7ifdyn
title: Wavelength131_Chunks.z15
DOI: 10.7910/dvn/tectsl/c1khag
title: Wavelength131_Chunks.z09
DOI: 10.7910/dvn/tectsl/cyp8fp
title: Wavelength131_Chunks.z12
DOI: 10.7910/dvn/tectsl/eqovhf
title: Wavelength131_Chunks.z14
DOI: 10.7910/dvn/tectsl/in1v2c
title: Wavelength131_Chunks.z11
DOI: 10.7910/dvn/tectsl/ts3hji
title: Wavelength131_Chunks.z10
DOI: 10.7910/dvn/dy1282/01bkhp
title: ReplicationCode_Study1.do
DOI: 10.7910/dvn/dy1282/gahoqw
title: Nepal_PB_RR.tab
DOI: 10.7910/dvn/dy1282/giqy36
title: Figure2_Replication.R
DOI: 10.7910/dvn/dy1282/qqzyz7
title: ReplicationCode_Study2.do
DOI: 10.7910/dvn/dy1282/ylyxgl
title: district_char.tab
DOI: 10.7910/dvn/dy1282/ztgtxt
title: conflict.tab
DOI: 10.7910/dvn/t9wesh/iwlvhp
title: sw_2.Rdata
DOI: 10.7910/dvn/t9wesh/kya1c5
title: summons_models.R
DOI: 10.7910/dvn/t9wesh/lbl5tq
title: summons_HAC_vc.Rdata
DOI: 10.7910/dvn/t9wesh/seyrsg
title: std_models_white_sus.Rdata
DOI: 10.7910/dvn/t9wesh/w3y9hz
title: summons_bandwidth.Rdata
DOI: 10.7910/dvn/tectsl/3whadh
title: Wavelength131_Chunks.z17
DOI: 10.7910/dvn/tectsl/4demsu
title: Wavelength131_Chunks.z19
DOI: 10.7910/dvn/tectsl/chnw0u
title: Wavelength131_Chunks.z16
DOI: 10.7910/dvn/tectsl/fw0cgc
title: Wavelength131_Chunks.z21
DOI: 10.7910/dvn/tectsl/jyppc7
title: Wavelength131_Chunks.z20
DOI: 10.7910/dvn/tectsl/zovwgu
title: Wavelength131_Chunks.z18
DOI: 10.7910/dvn/dy1282/bifx1e
title: Z01A.tab
DOI: 10.7910/dvn/dy1282/eeke6v
title: Study2_FINAL.tab
DOI: 10.7910/dvn/dy1282/lvrvsw
title: Z07A.tab
DOI: 10.7910/dvn/dy1282/uwd3ok
title: trafficking_nepal.tab
DOI: 10.7910/dvn/t9wesh/amknhe
title: sw_hom.Rdata
DOI: 10.7910/dvn/t9wesh/bl1fnn
title: vcovCluster.R
DOI: 10.7910/dvn/t9wesh/ct70ws
title: weapon_HAC_vc.Rdata
DOI: 10.7910/dvn/t9wesh/ivicad
title: white_bg_HAC_vc.Rdata
DOI: 10.7910/dvn/t9wesh/jmwgbc
title: weapon_models_batch.R
DOI: 10.7910/dvn/t9wesh/mi322v
title: uniform_HAC_vc.Rdata
DOI: 10.7910/dvn/t9wesh/wzvpno
title: uniform_data.Rdata
DOI: 10.7910/dvn/tectsl/apcu9b
title: Wavelength131_Chunks.z28
DOI: 10.7910/dvn/tectsl/fspwqj
title: Wavelength131_Chunks.z22
DOI: 10.7910/dvn/tectsl/gih2jr
title: Wavelength131_Chunks.z27
DOI: 10.7910/dvn/tectsl/hy2bzg
title: Wavelength131_Chunks.z24
DOI: 10.7910/dvn/tectsl/k2apqt
title: Wavelength131_Chunks.z26
DOI: 10.7910/dvn/tectsl/mouwxr
title: Wavelength131_Chunks.z25
DOI: 10.7910/dvn/tectsl/znizma
title: Wavelength131_Chunks.z23
DOI: 10.7910/dvn/t9wesh/krzh2y
title: white_bg_interact_bandwidth.Rdata
DOI: 10.7910/dvn/t9wesh/m1qtzx
title: white_interact_bandwidth.Rdata
DOI: 10.7910/dvn/t9wesh/v0qz48
title: white_sus_HAC_vc.Rdata
DOI: 10.7910/dvn/tectsl/3vziog
title: Wavelength131_Chunks.z31
DOI: 10.7910/dvn/tectsl/6cfpyb
title: Wavelength131_Chunks.z29
DOI: 10.7910/dvn/tectsl/6q4b3n
title: Wavelength131_Chunks.z33
DOI: 10.7910/dvn/tectsl/fnl6ty
title: Wavelength131_Chunks.z34
DOI: 10.7910/dvn/tectsl/on2cz8
title: Wavelength131_Chunks.z32
DOI: 10.7910/dvn/tectsl/uu0o9o
title: Wavelength131_Chunks.z30
DOI: 10.7910/dvn/y5ix90/24dsau
title: Hyperparameter settings of the baseline methods.pdf

description: Hyperparameter settings of the baseline methods. All the hyperparameter settings of the baseline methods used to compare with our MSDT algorithm are described in the attachment file.
DOI: 10.7910/dvn/y5ix90/cffsid
title: Metadata of The Datasets.pdf

description: The metadata of the experimental datasets. For the experiments in the MSDT algorithm, we have selected a total of 4 datasets. Each metadata of the datasets is described in this attachment file.
DOI: 10.7910/dvn/tectsl/fmleew
title: Wavelength131_Chunks.z40
DOI: 10.7910/dvn/tectsl/gd6uy4
title: Wavelength131_Chunks.z39
DOI: 10.7910/dvn/tectsl/ghnzb7
title: Wavelength131_Chunks.z35
DOI: 10.7910/dvn/tectsl/gyzbfn
title: Wavelength131_Chunks.z38
DOI: 10.7910/dvn/tectsl/ih3pnc
title: Wavelength131_Chunks.z37
DOI: 10.7910/dvn/tectsl/kt6v5l
title: Wavelength131_Chunks.z36
DOI: 10.7910/dvn/y5ix90/4fextv
title: msdt2-single-valued-ExpIII.2.accdb

description: The msdt2-single-valued dataset has three large single-valued and sequential-labeled datasets with α = 3..5. Since these baseline methods cannot handle data with multi-valued features, we consider the dataset with only single-valued features a special case for MSDT; we therefore remove all the three multi-valued features of the large dataset in Experiment III.1. Besides, we should further revise the five functions mentioned in Experiment II, because the multi-valued features constitute some of the conditions of those functions. The revised functions can be accessed at our data repository over the Harvard Dataverse repository. The number of various sequential-labels is 47 while α = 3; 243 while α = 4; and 878 while α = 5.
DOI: 10.7910/dvn/y5ix90/rgc5jm
title: msdt2-multi-valued-ExpIII.1.accdb

description: This dataset is parts of the msdt2-multi-valued dataset for Experiment III.1. Please refer to the description of msdt2-multi-valued-ExpII.accdb.
DOI: 10.7910/dvn/y5ix90/svlkem
title: msdt1-cdnow-rfm-ExpI.2.accdb

description: The CDNow-RFM dataset is the other of the two small real-life dataset candidates to be selected as a baseline dataset. In Experiment I.2, the features and the sequences of the CDNow-RFM dataset are extracted and summarized from CDNow_sample dataset (Fader and Hardie 2001) containing 2,357 online buyers about their purchasing transaction records from Jan. 1997 to June 1998, which can be accessed at http://www.brucehardie.com/datasets/. The number of various sequential-labels is 12 when the windows size = 2; and it is 33 when the windows size = 3. Reference: Fader, P. S. and Hardie, B. G. S. (2001). Forecasting Repeat Sales at CDNOW: A Case Study. Interfaces, 31(3), Part 2 of 2, S94-S107.
DOI: 10.7910/dvn/y5ix90/wflbse
title: msdt1-tourist-ExpI.1.accdb

description: The Tourist dataset is one of the two small real-life dataset candidates to be selected as a baseline dataset. In Experiment I.1, the Tourist dataset contains the records of 100 offline buyers who registered their profiles in any online websites first and then consumed tour itinerary services in brick-and-mortar stores offline. The item-sequences were surveyed and sampled from their purchased itinerary services across five districts of Taiwan during the year of 2014. The number of various sequential-labels is 40.
DOI: 10.7910/dvn/y5ix90/ylkhr9
title: msdt2-multi-valued-ExpII.accdb

description: The msdt2-multi-valued dataset for Exp. II has three large multi-valued and sequential-labeled datasets with α = 3..5. We apply the MSDT algorithm on handling a large dataset of tourists. The large dataset has the same features and values as the dataset used by both the multi-valued and multi-labeled algorithms of MMC and MMDT, except it has two additional attributes, one for item-sequences and the other for sequential-label. And, three features of the dataset are multi-valued. To learn a classifier from incrementally-added sequences of training instances within some successive sliding windows per classification lifecycle, we set the user-specified parameters that the sliding window sizes, α = 3..5. Therefore, the value of the “sequences” attribute is a set of item-sequences with lengths from 3 to 5, which correspond three most recent sliding windows respectively with incrementally-added sizes. We thus have three large datasets of 3-sequence, 4-sequence and 5-sequence. The item-sequences of each record are generated by the combination of the five functions, which can be accessed at our data repository over the Harvard Dataverse repository. The number of various sequential-labels is 10 while α = 3; 13 while α = 4; and 10 while α = 5. All the experiments use 5,000 records as the test dataset. The size of 8 training-set are 90, 1,000, 4,000, 6,000, 8,000, 10,000, 12,000 and 14,000 records respectively.
DOI: 10.7910/dvn/ikibtx/a0n8jw
title: Correlates_Figure5_2016_07_12.do
DOI: 10.7910/dvn/ikibtx/cjwajz
title: 2016_02_09_uem.tab
DOI: 10.7910/dvn/ikibtx/fkr435
title: Correlates_Figure3_2016_07_10.do
DOI: 10.7910/dvn/ikibtx/qy5ksx
title: Correlates_Figure4_2016_11_1.do
DOI: 10.7910/dvn/ikibtx/r6p0dj
title: Correlates_Figure2_2016_07_10.do
DOI: 10.7910/dvn/ikibtx/rcopqq
title: Correlates_Figure1_2016_07_10.do
DOI: 10.7910/dvn/tectsl/kclisa
title: Wavelength131_Chunks.z41
DOI: 10.7910/dvn/tectsl/qtdxlk
title: Wavelength131_Chunks.zip
DOI: 10.7910/dvn/tectsl/qzbysa
title: Wavelength131_Chunks.z42
DOI: 10.7910/dvn/ikibtx/5jc1cj
title: Correlates_Figure6_2016_07_10.do
DOI: 10.7910/dvn/ikibtx/aiesrz
title: Correlates_Figure7_2016_07_10.do
DOI: 10.7910/dvn/ikibtx/g6idwc
title: Correlates_Table8_2016_07_10.do
DOI: 10.7910/dvn/ikibtx/mrwdwe
title: Correlates_Table_1_2_4_5_2016_07_10.do
DOI: 10.7910/dvn/ikibtx/pq8gkd
title: Correlates_Table7_2016_07_10.do
DOI: 10.7910/dvn/ikibtx/s43msq
title: Correlates_Table6_2016_07_24.do
DOI: 10.7910/dvn/itydk1/hxyfoz
title: dejure.tab
DOI: 10.7910/dvn/itydk1/kxaioi
title: 061124-thesis-turnover.tab
DOI: 10.7910/dvn/ek1rtr/ajzy0v
title: PRQ Replication Data.tab
DOI: 10.7910/dvn/itydk1/cl1pdr
title: othervars.tab
DOI: 10.7910/dvn/itydk1/gilxdo
title: governments.tab
DOI: 10.7910/dvn/itydk1/pdrvzc
title: executives.r
DOI: 10.7910/dvn/4pjtgu/1usica
title: braithwaite_lemke replication do file.do
DOI: 10.7910/dvn/4pjtgu/45oi9l
title: file note.rtf
DOI: 10.7910/dvn/4pjtgu/8lhawr
title: data for testing.tab
DOI: 10.7910/dvn/4pjtgu/v0ymnr
title: gibler and miller rep do file.do
DOI: 10.7910/dvn/4pjtgu/vbfgyd
title: B&L_CMPS with revised data.tab
DOI: 10.7910/dvn/4pjtgu/sszyvi
title: weeks replication do file.do
DOI: 10.7910/dvn/4pjtgu/xmrti4
title: WeeksIO.tab
DOI: 10.7910/dvn/ro8itp/adzqfk
title: replication log.smcl
DOI: 10.7910/dvn/ro8itp/dw4y9v
title: gibler_little_repdata.tab
DOI: 10.7910/dvn/ro8itp/hee8si
title: protest only do file.do
DOI: 10.7910/dvn/ro8itp/i404tu
title: table1repfile.do
DOI: 10.7910/dvn/sigipu/d5xdsd
title: ar1_like.m

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DOI: 10.7910/dvn/sigipu/mtxdeo
title: accumulate.m

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DOI: 10.7910/dvn/sigipu/wg9uiv
title: arf_d.m

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DOI: 10.7910/dvn/sigipu/4s8ydf
title: ar.m

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DOI: 10.7910/dvn/sigipu/k0hdgv
title: ar_g.m

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DOI: 10.7910/dvn/sigipu/k0t1cy
title: ar_gd.m

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DOI: 10.7910/dvn/sigipu/pjmhht
title: BaselineModel.ox

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DOI: 10.7910/dvn/sigipu/sdkwkh
title: arf.m

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DOI: 10.7910/dvn/sigipu/jp5yan
title: BaselineModel.ox.bak

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title: becmf_gd.m

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title: becmf_d.m

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title: becm_d.m

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title: becm_g.m

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DOI: 10.7910/dvn/sigipu/9tjznt
title: becm.m

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DOI: 10.7910/dvn/sigipu/jw2rd4
title: beta_cdf.m

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title: becm_gd.m

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title: becmf.m

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title: bingen.m

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DOI: 10.7910/dvn/sigipu/gpm8me
title: beta_inv.m

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DOI: 10.7910/dvn/sigipu/jyueds
title: bincoef.m

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DOI: 10.7910/dvn/sigipu/keqy5q
title: beta_rnd.m

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title: beta_d.m

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DOI: 10.7910/dvn/sigipu/wqmwpn
title: beta_pdf.m

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DOI: 10.7910/dvn/xchqqt/0lfdno
title: 03. MD2324 X SEA5 Greenhouse 2011.tab

description: Evaluation of root traits (Greenhouse conditions) in RILs under irrigated and drought conditions
DOI: 10.7910/dvn/xchqqt/1ila58
title: 01. Dictonary.xls

description: Document detailing the traits used
DOI: 10.7910/dvn/xchqqt/a4voo3
title: 02. MD2324 X SEA5 Field 2003 2004 2007.tab

description: Evaluation of shoot traits (Field conditions) in RILs under irrigated and drought conditions in three years 2003, 2004 and 2007
DOI: 10.7910/dvn/gmfctr/izqodz
title: NewsArticles.csv
DOI: 10.7910/dvn/sigipu/5jmbdl
title: bino_pdf.m

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title: blockdiag.m

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title: boxcox_d.m

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title: Cftl_flows.m

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title: Cftl_women.m

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title: RTC_Data&Programs.tab

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description: :unav
DOI: 10.7910/dvn/sigipu/zkruzw
title: dmult.m

description: :unav
DOI: 10.15468/dl.9nj3py
title: Occurrence Download

description: A dataset containing 2178 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Country is Germany",
 "DecimalLongitude is greater than or equal to 7.15134233744581",
 "DecimalLongitude is less than 7.15440189063021",
 "DecimalLatitude is greater than or equal to 47.27011",
 "DecimalLatitude is less than or equal to 55.05864"
 ]
}

 The dataset includes 2178 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028514-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/80wuqb/4z17ml
title: 2pl_theta_mul.tab
DOI: 10.7910/dvn/80wuqb/gjwroq
title: 3pl_dif_para.csv
DOI: 10.7910/dvn/80wuqb/vz6xkw
title: 3pl_dif_theta.tab
DOI: 10.7910/dvn/80wuqb/wcwx2i
title: 3pl_para2.tab
DOI: 10.7910/dvn/80wuqb/wm34qq
title: 3pl_para_anes.tab
DOI: 10.7910/dvn/sigipu/gkyf7h
title: fdis_inv.m

description: :unav
DOI: 10.7910/dvn/sigipu/gllj42
title: ecm.m

description: :unav
DOI: 10.7910/dvn/sigipu/uzbwpc
title: ecm_notes.m

description: :unav
DOI: 10.7910/dvn/sigipu/vgwjso
title: fdis_d.m

description: :unav
DOI: 10.7910/dvn/sigipu/wdmwii
title: ecmftest.m

description: :unav
DOI: 10.7910/dvn/sigipu/xquwew
title: fdis_cdf.m

description: :unav
DOI: 10.7910/dvn/80wuqb/88gdsv
title: ANES_eggs4_replication.R
DOI: 10.7910/dvn/80wuqb/mpq1yt
title: 3pl_theta_mul.tab
DOI: 10.7910/dvn/80wuqb/mtzc1y
title: 3pl_para_mul.tab
DOI: 10.7910/dvn/80wuqb/x5asvr
title: anes_specialstudies_2012egss4.tab
DOI: 10.7910/dvn/sigipu/nxcuxq
title: fdis_prb.m

description: :unav
DOI: 10.7910/dvn/sigipu/qc6owl
title: felogit.m

description: :unav
DOI: 10.7910/dvn/sigipu/qeus7f
title: fdis_rnd.m

description: :unav
DOI: 10.7910/dvn/sigipu/shmvav
title: felogit_lik.m

description: :unav
DOI: 10.7910/dvn/sigipu/wdmf3e
title: felogit_demo.m

description: :unav
DOI: 10.7910/dvn/sigipu/xpxfkr
title: fdis_pdf.m

description: :unav
DOI: 10.7910/dvn/80wuqb/hg65wm
title: guess_dif_theta.tab
DOI: 10.7910/dvn/80wuqb/lyuoue
title: guess_para_anes.tab
DOI: 10.7910/dvn/80wuqb/vs4lbu
title: guess_dif_para.csv
DOI: 10.7910/dvn/80wuqb/wvqalz
title: guess_para2.tab
DOI: 10.7910/dvn/80wuqb/ygudge
title: appendix_analysis.R
DOI: 10.7910/dvn/sigipu/9opge7
title: find_bigd.m

description: :unav
DOI: 10.7910/dvn/sigipu/cbh3gl
title: Figure_2_data.tab

description: :unav
DOI: 10.7910/dvn/sigipu/h5ry7p
title: Fig_HzdRates.m

description: :unav
DOI: 10.7910/dvn/sigipu/ohfkeb
title: felogit.zip

description: :unav
DOI: 10.7910/dvn/sigipu/xlfoij
title: Figure_8_data.tab

description: :unav
DOI: 10.7910/dvn/sigipu/zvtob0
title: Figure_3_data.tab

description: :unav
DOI: 10.7910/dvn/80wuqb/4bcocm
title: irt_3pl_dif.R
DOI: 10.7910/dvn/80wuqb/jgxznz
title: guess_theta_mul.tab
DOI: 10.7910/dvn/80wuqb/kvhiel
title: irt_2pl_dif.R
DOI: 10.7910/dvn/80wuqb/phbxwl
title: irt_3pl.R
DOI: 10.7910/dvn/80wuqb/vy6cnr
title: guess_para_mul.tab
DOI: 10.7910/dvn/80wuqb/zeyawl
title: irt_2pl.R
DOI: 10.7910/dvn/ihgzil/xyu63v
title: Clark_JHRdata.dta

description: :unav
DOI: 10.7910/dvn/sigipu/6y5ruq
title: Flows_m1624.tab

description: :unav
DOI: 10.7910/dvn/sigipu/lixa4a
title: Flows__6585.tab

description: :unav
DOI: 10.7910/dvn/sigipu/njzaes
title: findnear.m

description: :unav
DOI: 10.7910/dvn/sigipu/ufznod
title: Flows_m2534.tab

description: :unav
DOI: 10.7910/dvn/sigipu/w6xrrw
title: find_big.m

description: :unav
DOI: 10.7910/dvn/80wuqb/139xdl
title: readme.rtf
DOI: 10.7910/dvn/80wuqb/nqhnsy
title: irt_guess.R
DOI: 10.7910/dvn/80wuqb/nsegwk
title: main_analysis.R
DOI: 10.7910/dvn/80wuqb/nysr6c
title: knowledge_functions.R
DOI: 10.7910/dvn/80wuqb/uj8fkz
title: irt_guess_dif.R
DOI: 10.7910/dvn/sigipu/fxgr9c
title: Flows_m5564.tab

description: :unav
DOI: 10.7910/dvn/sigipu/gud0br
title: Flows_m3544.tab

description: :unav
DOI: 10.7910/dvn/sigipu/ldxbz5
title: Flows_w2534.tab

description: :unav
DOI: 10.7910/dvn/sigipu/ojakje
title: Flows_w1624.tab

description: :unav
DOI: 10.7910/dvn/sigipu/pdw89f
title: Flows_m4554.tab

description: :unav
DOI: 10.7910/dvn/sigipu/xxmw4r
title: Flows_w3544.tab

description: :unav
DOI: 10.7910/dvn/80wuqb/kw5f5p
title: sanmartin_para_anes.tab
DOI: 10.7910/dvn/80wuqb/ploukr
title: sanmartin_para.tab
DOI: 10.7910/dvn/80wuqb/uuj9fa
title: teds2012_ind.tab
DOI: 10.7910/dvn/ancvvy/j91j2g
title: Image_Parameters_Chunks.z04
DOI: 10.7910/dvn/ancvvy/moay69
title: Image_Parameters_Chunks.z01
DOI: 10.7910/dvn/ancvvy/rbk3yk
title: Image_Parameters_Chunks.z03
DOI: 10.7910/dvn/ancvvy/tfyp3t
title: Image_Parameters_Chunks.z02
DOI: 10.7910/dvn/ancvvy/x3anpu
title: Image_Parameter_Column_Names.txt
DOI: 10.7910/dvn/sigipu/8qhqzs
title: Flows_w4554.tab

description: :unav
DOI: 10.7910/dvn/sigipu/arocdg
title: Flows_w5564.tab

description: :unav
DOI: 10.7910/dvn/sigipu/cebgl3
title: fturns.m

description: :unav
DOI: 10.7910/dvn/sigipu/x9dhzv
title: fturns_d.m

description: :unav
DOI: 10.7910/dvn/sigipu/y6cizn
title: gamm_cdf.m

description: :unav
DOI: 10.7910/dvn/zulmoy/3cqfew
title: keywords_1976-1980_kwLimit100000.0_dispth0.06_ethunit4.1e-05.csv
DOI: 10.7910/dvn/zulmoy/dklsew
title: keywords_1977-1981_kwLimit100000.0_dispth0.06_ethunit4.1e-05.csv
DOI: 10.7910/dvn/zulmoy/dxbswi
title: keywords_1979-1983_kwLimit100000.0_dispth0.06_ethunit4.1e-05.csv
DOI: 10.7910/dvn/zulmoy/g6snqs
title: keywords_1978-1982_kwLimit100000.0_dispth0.06_ethunit4.1e-05.csv
DOI: 10.7910/dvn/zulmoy/y7i3zi
title: classification_window5_kwLimit100000_dispth0.06_ethunit4.1e-05.tar.gz
DOI: 10.7910/dvn/ancvvy/a6law1
title: Image_Parameters_Chunks.z05
DOI: 10.7910/dvn/ancvvy/ddxvuh
title: Image_Parameters_Chunks.z10
DOI: 10.7910/dvn/ancvvy/jtlbft
title: Image_Parameters_Chunks.z08
DOI: 10.7910/dvn/ancvvy/mjitrh
title: Image_Parameters_Chunks.z07
DOI: 10.7910/dvn/ancvvy/o00iib
title: Image_Parameters_Chunks.z09
DOI: 10.7910/dvn/ancvvy/s5hobc
title: Image_Parameters_Chunks.z06
DOI: 10.7910/dvn/sigipu/2w69ho
title: gamm_rnd2.m

description: :unav
DOI: 10.7910/dvn/sigipu/a6kb7r
title: gamm_pdf.m

description: :unav
DOI: 10.7910/dvn/sigipu/d7k4wu
title: gamm_d.m

description: :unav
DOI: 10.7910/dvn/sigipu/gkckh6
title: gamm_rnd3.m

description: :unav
DOI: 10.7910/dvn/sigipu/kv7gbp
title: gamm_rnd.m

description: :unav
DOI: 10.7910/dvn/sigipu/zyvmus
title: gamm_inv.m

description: :unav
DOI: 10.7910/dvn/zulmoy/1gk7fp
title: keywords_1983-1987_kwLimit100000.0_dispth0.06_ethunit4.1e-05.csv
DOI: 10.7910/dvn/zulmoy/9xjqhx
title: keywords_1980-1984_kwLimit100000.0_dispth0.06_ethunit4.1e-05.csv
DOI: 10.7910/dvn/zulmoy/cryiuu
title: keywords_1984-1988_kwLimit100000.0_dispth0.06_ethunit4.1e-05.csv
DOI: 10.7910/dvn/zulmoy/eduktc
title: keywords_1982-1986_kwLimit100000.0_dispth0.06_ethunit4.1e-05.csv