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Releases: fipelle/MessyTimeSeriesOptim.jl

Simplified initialisation

14 Feb 15:50
@fipelle fipelle
v0.2.3
333164f
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Simplified initialisation Latest
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Merge pull request #24 from fipelle/dev

Further simplifications in the initialisation
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Multivariate initialisation

04 Dec 21:43
@fipelle fipelle
v0.2.2
c4f24b6
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Multivariate initialisation 
Merge pull request #23 from fipelle/dev

Multivariate initialisation
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Bug fix for new DFM initialisation

18 Oct 22:50
@fipelle fipelle
v0.2.1
64ca8e0
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Bug fix for new DFM initialisation 
Merge pull request #22 from fipelle/dev

Update to 0.2.1
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Fix in initialisation for DFM models

19 Sep 20:53
@fipelle fipelle
v0.2.0
1a3c7ce
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Fix in initialisation for DFM models 
Merge pull request #21 from fipelle/dev

New version: fix in init
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Patch release: initialise idio cycle as ar(1)

24 Dec 15:05
@fipelle fipelle
v0.1.8
008faca
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Patch release: initialise idio cycle as ar(1) 
Merge pull request #20 from fipelle/dev_init

Initialise idio cycle as ar(1)
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Use of compute_scaling_factors(...) within validation + bug fixes

09 Dec 18:14
@fipelle fipelle
v0.1.7
32e783a
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Use of compute_scaling_factors(...) within validation + bug fixes 
Merge pull request #19 from fipelle/fipelle-patch-1

Update LICENSE
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v0.1.6

27 Jul 12:31
@fipelle fipelle
v0.1.6
770d5b3
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v0.1.6

Added support the new sequential approach for filtering and smoothing in MessyTimeSeries.jl

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v0.1.5

21 Jul 23:22
@fipelle fipelle
v0.1.5
080a9ca
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v0.1.5

Patch release

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v0.1.4

18 Jul 23:48
@fipelle fipelle
v0.1.4
96a49d4
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v0.1.4

Implemented Kitagawa's trend for non-stationary DFMs

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v0.1.3

23 Mar 13:46
@github-actions github-actions
v0.1.3
edf4ced
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v0.1.3

MessyTimeSeriesOptim v0.1.3

Diff since v0.1.2

Closed issues:

  • Get rid of StableRNG? (#6)

Merged pull requests:

  • Logo (#8) (@fipelle)
  • Implemented N as a sparse matrix -> notable memory improvements for high-dimensional problems (#9) (@fipelle)

Contributors

fipelle
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