add Bivariate Extreme Value Copulas #208

Santymax98 · 2024-07-25T18:05:40Z

new file:   docs/src/extremevalue/generalities.md
modified:   src/Copulas.jl
new file:   src/ExtremeValue.jl
new file:   src/ExtremeValueCopulas/AsymGalambosCopula.jl
new file:   src/ExtremeValueCopulas/AsymLogCopula.jl
new file:   src/ExtremeValueCopulas/AsymMixedCopula.jl
new file:   src/ExtremeValueCopulas/BC2Copula.jl
new file:   src/ExtremeValueCopulas/CuadrasAugeCopula.jl
new file:   src/ExtremeValueCopulas/GalambosCopula.jl
new file:   src/ExtremeValueCopulas/HuslerReissCopula.jl
new file:   src/ExtremeValueCopulas/LogCopula.jl
new file:   src/ExtremeValueCopulas/MOCopula.jl
new file:   src/ExtremeValueCopulas/MixedCopula.jl
new file:   src/ExtremeValueCopulas/tEVCopula.jl
new file:   src/UnivariateDistribution/ExtremeDist.jl
new file:   test/Extreme_value_test.jl

new file: docs/src/extremevalue/generalities.md modified: src/Copulas.jl new file: src/ExtremeValue.jl new file: src/ExtremeValueCopulas/AsymGalambosCopula.jl new file: src/ExtremeValueCopulas/AsymLogCopula.jl new file: src/ExtremeValueCopulas/AsymMixedCopula.jl new file: src/ExtremeValueCopulas/BC2Copula.jl new file: src/ExtremeValueCopulas/CuadrasAugeCopula.jl new file: src/ExtremeValueCopulas/GalambosCopula.jl new file: src/ExtremeValueCopulas/HuslerReissCopula.jl new file: src/ExtremeValueCopulas/LogCopula.jl new file: src/ExtremeValueCopulas/MOCopula.jl new file: src/ExtremeValueCopulas/MixedCopula.jl new file: src/ExtremeValueCopulas/tEVCopula.jl new file: src/UnivariateDistribution/ExtremeDist.jl new file: test/Extreme_value_test.jl

Santymax98 · 2024-07-25T18:12:12Z

Hi dear @lrnv Could you help me find out an error that appears in tEVCopula? Maybe the error is that we don't have StatsFuns as a deps??

tEVCopula - sampling, pdf, cdf: Test Failed at /home/runner/work/Copulas.jl/Copulas.jl/test/Extreme_value_test.jl:293
  Expression: e isa ArgumentError
   Evaluated: UndefVarError(:StatsFuns) isa ArgumentError
Stacktrace:
 [1] macro expansion
   @ ~/work/Copulas.jl/Copulas.jl/test/Extreme_value_test.jl:293 [inlined]
 [2] macro expansion
   @ /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.6/Test/src/Test.jl:1151 [inlined]
 [3] top-level scope
   @ ~/work/Copulas.jl/Copulas.jl/test/Extreme_value_test.jl:262

The other errors are something related to

test/margins_uniformity.jl | 1251 11 1262

I think they have nothing to do with Extreme Value Copulas

lrnv · 2024-07-25T18:25:57Z

I will take a look tonight -- stuck at a airport. The margins_uniformity checks that every copula has uniform margins, and if your copula do not pass the test then yes it's an issue :)

Santymax98 · 2024-07-25T18:35:14Z

You are travelling? for work or vacation? hahaha a well deserved rest. It's strange because before I did an exhaustive review of the graphics, the marginalia and some comparisons with other codes. The algorithm follows exactly what is described in the article, I think we can check it when you are free. El El jue, 25 jul. 2024 a la(s) 13:26, Oskar Laverny < ***@***.***> escribió:

…

I will take a look tonight -- stuck at a airport. The margins_uniformity checks that every copula has uniform margins, and if your copula do not pass the test then yes it's an issue :) — Reply to this email directly, view it on GitHub <#208 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/A7PTWNSB3PLUSVHZAG5DB7DZOE7MXAVCNFSM6AAAAABLPBR3F6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDENJRGE2DIOJWG4> . You are receiving this because you authored the thread.Message ID: ***@***.***>

lrnv · 2024-07-25T21:19:27Z

For work, but then a flights got cancelled... So, does hits PR replaces #205 ? If yes, we could close #205 then. Looking at the errors right now will be back soon

lrnv · 2024-07-25T21:44:44Z

So, margins_uniformity.jl is simply a script that checks for uniformity of the margins of the copulas. I yells when there are copulas types without instances tested, which was your case. I added some instances of your types in the list.

Now it yells because some of them do not produce marignals uniform enough. We have to investigate why -- maybe the way i'm checking uniformity is not right !

Santymax98 · 2024-07-25T21:59:43Z

Yup, this replaces #205 ;

The algorithm I used is the one presented in this reference Ghoudi, K., Khoudraji, A., & Rivest, E. L. P. (1998). Propriétés statistiques des copules de valeurs extrêmes bidimensionnelles. Canadian Journal of Statistics, 26(1), 187-197. in section 3.

modified: src/Copulas.jl modified: src/ExtremeValueCopulas/tEVCopula.jl modified: src/UnivariateDistribution/ExtremeDist.jl

into extreme_value

into pr/Santymax98/208

lrnv · 2024-07-25T23:21:05Z

So I temporarily removed the KS test so that we can concentrate on the rest for the moment.

I have weird behaviors of HuslerReis (and also tEV it seems ?) on the cdf when one of the two values is 1 :

julia> C = HuslerReissCopula(0.1)
HuslerReissCopula{Float64}(θ=0.1)

julia> cdf(C, [1,0.7])
ERROR: DomainError with -Inf:
log was called with a negative real argument but will only return a complex result if called with a complex argument. Try log(Complex(x)).
Stacktrace:
 [1] throw_complex_domainerror(f::Symbol, x::Float64)
   @ Base.Math .\math.jl:33
 [2] _log(x::Float64, base::Val{:ℯ}, func::Symbol)
   @ Base.Math .\special\log.jl:301
 [3] log
   @ .\special\log.jl:267 [inlined]
 [4] ℓ(H::HuslerReissCopula{Float64}, t::Vector{Float64})
   @ Copulas c:\Users\lrnv\.julia\dev\Copulas\src\ExtremeValueCopulas\HuslerReissCopula.jl:45
 [5] _cdf(C::HuslerReissCopula{Float64}, u::Vector{Float64})
   @ Copulas c:\Users\lrnv\.julia\dev\Copulas\src\ExtremeValue.jl:25
 [6] cdf(C::HuslerReissCopula{Float64}, u::Vector{Float64})
   @ Copulas c:\Users\lrnv\.julia\dev\Copulas\src\Copula.jl:19
 [7] top-level scope
   @ REPL[83]:1

julia>

And this is precisely the checks I am doing : checking that cdf(, [1,....1, x, 1.... 1]) == x for any x to ensure margins uniformity.

Maybe you could ammend your implementation to return the correct limit instead of failling in some cases ? maybe there are logs that need to be more carefully implemented or exp(log(..)) that coul dbe removed, or something like that ?

Santymax98 · 2024-07-25T23:26:59Z

I'm going to review the edge cases when they are 1 and 0, the way to get the cdf is exp(-\ell)

lrnv · 2024-07-25T23:27:48Z

Ok i think i managed to fix some of the domain errors by replacing a t = -log.(u) by t = abs.(log.(u)), where 0 <= u <= 1. This is sementically the same but then -log(1) is -0 while you intended 0.

Runnig the full test suite again to see what's next :)

modified: src/ExtremeValueCopulas/LogCopula.jl

Santymax98 · 2024-07-25T23:32:28Z

Using absolute value was a good move

lrnv · 2024-07-25T23:33:39Z

Now looks like MOCopula is failling the uniformity test of its marginals:

(C, u) = (Copulas.MOCopula{Float64}(λ1=0.1, λ2=0.2, λ12=0.3), [0.30184329672330246, 1.0])
Generic tests on every copulas: Test Failed at C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
  Expression: ≈(cdf(C, u), val, atol = 1.0e-5)
   Evaluated: 0.3835528626511967 ≈ 0.30184329672330246 (atol=1.0e-5)

Stacktrace:
 [1] macro expansion
   @ C:\Users\lrnv\.julia\juliaup\julia-1.10.0+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Test\src\Test.jl:672 [inlined]
 [2] top-level scope
   @ C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
(C, u) = (Copulas.MOCopula{Float64}(λ1=0.1, λ2=0.2, λ12=0.3), [0.6965294668307551, 1.0])
Generic tests on every copulas: Test Failed at C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
  Expression: ≈(cdf(C, u), val, atol = 1.0e-5)
   Evaluated: 0.7487754473247006 ≈ 0.6965294668307551 (atol=1.0e-5)

Stacktrace:
 [1] macro expansion
   @ C:\Users\lrnv\.julia\juliaup\julia-1.10.0+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Test\src\Test.jl:672 [inlined]
 [2] top-level scope
   @ C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
(C, u) = (Copulas.MOCopula{Float64}(λ1=0.1, λ2=0.2, λ12=0.3), [0.6770337002357543, 1.0])
Generic tests on every copulas: Test Failed at C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
  Expression: ≈(cdf(C, u), val, atol = 1.0e-5)
   Evaluated: 0.7319614847835554 ≈ 0.6770337002357543 (atol=1.0e-5)

Stacktrace:
 [1] macro expansion
   @ C:\Users\lrnv\.julia\juliaup\julia-1.10.0+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Test\src\Test.jl:672 [inlined]
 [2] top-level scope
   @ C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
(C, u) = (Copulas.MOCopula{Float64}(λ1=0.1, λ2=0.2, λ12=0.3), [0.5793654774234129, 1.0])
Generic tests on every copulas: Test Failed at C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
  Expression: ≈(cdf(C, u), val, atol = 1.0e-5)
   Evaluated: 0.6461927642785321 ≈ 0.5793654774234129 (atol=1.0e-5)

Stacktrace:
 [1] macro expansion
   @ C:\Users\lrnv\.julia\juliaup\julia-1.10.0+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Test\src\Test.jl:672 [inlined]
 [2] top-level scope
   @ C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
(C, u) = (Copulas.MOCopula{Float64}(λ1=0.1, λ2=0.2, λ12=0.3), [0.6629483465032526, 1.0])
Generic tests on every copulas: Test Failed at C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
  Expression: ≈(cdf(C, u), val, atol = 1.0e-5)
   Evaluated: 0.7197534469127619 ≈ 0.6629483465032526 (atol=1.0e-5)

Stacktrace:
 [1] macro expansion
   @ C:\Users\lrnv\.julia\juliaup\julia-1.10.0+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Test\src\Test.jl:672 [inlined]
 [2] top-level scope
   @ C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
(C, u) = (Copulas.MOCopula{Float64}(λ1=0.1, λ2=0.2, λ12=0.3), [0.30184329672330246, 1.0])
Generic tests on every copulas: Test Failed at C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
  Expression: ≈(cdf(C, u), val, atol = 1.0e-5)
   Evaluated: 0.3835528626511967 ≈ 0.30184329672330246 (atol=1.0e-5)

Stacktrace:
 [1] macro expansion
   @ C:\Users\lrnv\.julia\juliaup\julia-1.10.0+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Test\src\Test.jl:672 [inlined]
 [2] top-level scope
   @ C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
(C, u) = (Copulas.MOCopula{Float64}(λ1=0.1, λ2=0.2, λ12=0.3), [0.6965294668307551, 1.0])
Generic tests on every copulas: Test Failed at C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
  Expression: ≈(cdf(C, u), val, atol = 1.0e-5)
   Evaluated: 0.7487754473247006 ≈ 0.6965294668307551 (atol=1.0e-5)

Stacktrace:
 [1] macro expansion
   @ C:\Users\lrnv\.julia\juliaup\julia-1.10.0+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Test\src\Test.jl:672 [inlined]
 [2] top-level scope
   @ C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
(C, u) = (Copulas.MOCopula{Float64}(λ1=0.1, λ2=0.2, λ12=0.3), [0.6770337002357543, 1.0])
Generic tests on every copulas: Test Failed at C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
  Expression: ≈(cdf(C, u), val, atol = 1.0e-5)
   Evaluated: 0.7319614847835554 ≈ 0.6770337002357543 (atol=1.0e-5)

Stacktrace:
 [1] macro expansion
   @ C:\Users\lrnv\.julia\juliaup\julia-1.10.0+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Test\src\Test.jl:672 [inlined]
 [2] top-level scope
   @ C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
(C, u) = (Copulas.MOCopula{Float64}(λ1=0.1, λ2=0.2, λ12=0.3), [0.5793654774234129, 1.0])
Generic tests on every copulas: Test Failed at C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
  Expression: ≈(cdf(C, u), val, atol = 1.0e-5)
   Evaluated: 0.6461927642785321 ≈ 0.5793654774234129 (atol=1.0e-5)

Stacktrace:
 [1] macro expansion
   @ C:\Users\lrnv\.julia\juliaup\julia-1.10.0+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Test\src\Test.jl:672 [inlined]
 [2] top-level scope
   @ C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
(C, u) = (Copulas.MOCopula{Float64}(λ1=0.1, λ2=0.2, λ12=0.3), [0.6629483465032526, 1.0])
Generic tests on every copulas: Test Failed at C:\Users\lrnv\.julia\dev\Copulas\test\margins_uniformity.jl:146
  Expression: ≈(cdf(C, u), val, atol = 1.0e-5)
   Evaluated: 0.7197534469127619 ≈ 0.6629483465032526 (atol=1.0e-5)

Basically you can verify it by runnig:

C = MOCopula(0.1,0.2,0.3)
u = [1, rand()]
v = [rand(), 1]
(cdf(C,u), u[2]) # should be equal
(cdf(C,v), v[1]) # should be equal

Moreover, it looks like it is OK for [1, rand()] but failling for [rand(), 1]. Maybe you need to check the implementation of this cdf ?

Santymax98 · 2024-07-25T23:40:40Z

using Distributions
using HypothesisTests
using TwinCopulas

function test_uniformity(data)
    n, m = size(data)
    results = []
    
    for i in 1:n
        sample = data[i, :]
        ks_test = ApproximateOneSampleKSTest(sample, Uniform(0, 1))
        p_value = pvalue(ks_test)
        push!(results, (i, p_value))
    end
    
    return results
end

cops = (AsymGalambosCopula(0.1, [0.2,0.6]),
        AsymLogCopula(1.2, [0.3,0.6]),
        BC2Copula(0.7,0.3),
        CuadrasAugeCopula(0.1),
        HuslerReissCopula(0.1),
        MixedCopula(0.2),
        MOCopula(0.1,0.2,0.3),
        )

for (i, C) in enumerate(cops)
    println("\nProbando copula $i: $(typeof(C))")
    data = rand(C, 1000) # Genera datos a partir de la copula

    results = test_uniformity(data)

    # Mostrar los resultados
    for (marginal, p_value) in results
        println("Marginal $marginal: p-value = $p_value")
        if p_value < 0.05
            println("Rechazamos la hipótesis nula de que la marginal $marginal proviene de una distribución uniforme.")
        else
            println("No podemos rechazar la hipótesis nula de que la marginal $marginal proviene de una distribución uniforme.")
        end
    end    
end

In my case I used this, and it checks uniformity for all, I have problems with Galambos and logistic (which should be equal to gumbel)

lrnv · 2024-07-25T23:42:48Z

The problem with this test is that it might just fail out of bad luck (that is the definition of a 5% p-value : in 5% of the cases it'll fail under H0)...

lrnv · 2024-07-25T23:43:13Z

You have missing references in the .bib : Joe1990, Ghoudi1998. can you add them ?

Santymax98 · 2024-07-25T23:44:12Z

You are right, I also noticed the bug in MOCopula, we could remove the function $\ell$ from the file and leave only $\isansA$

Santymax98 · 2024-07-25T23:45:46Z

I'm terrible at placing citations, however I think I can look them up and start completing each one of them. I think I only put the names of the references without links, right, or .bib, right?

lrnv · 2024-07-25T23:45:54Z

The abstract type ExtremeValueCopula is not documented, while you make a reference to it in the docs. Maybe it shoul dbe documented ?

lrnv · 2024-07-25T23:46:25Z

I'm terrible at placing citations, however I think I can look them up and start completing each one of them. I think I only put the names of the references without links, right, or .bib, right?

Yes you wrte the citations corectly, just forgot to add them to the .bib file

lrnv · 2024-07-25T23:46:56Z

You are right, I also noticed the bug in MOCopula, we could remove the function ℓ from the file and leave only \isansA

If it is enough, yes you can try that

Santymax98 · 2024-07-29T16:29:26Z

Hi Oskar, sorry for not responding sooner, I'm a little sick but I'll start going over each aspect to find the solution. El El lun, 29 jul. 2024 a la(s) 3:49, Oskar Laverny < ***@***.***> escribió:

…

@Santymax98 <https://github.com/Santymax98> Ok i put a bit of an effort to fix the references. On top of the two or three coments that are still unresolved in this thread, there are still a few issues: - MOCopula still failling. - Docstring for the abstract type ExtremeValueCopula is missing - The documentation is not very clear about references for the sampling algorithm, neither on which one of the two is used by the code. I am now waiting for your input. Once you have these few things figured out, we can merge this :) — Reply to this email directly, view it on GitHub <#208 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/A7PTWNUWJRUFULG3QGOOB33ZOX6YXAVCNFSM6AAAAABLPBR3F6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDENJVGM3DAMJSHE> . You are receiving this because you were mentioned.Message ID: ***@***.***>

lrnv · 2024-07-29T17:06:33Z

Sorry to hear that, hope you'll get better soon ! :/

Yeah take your time, there is no rush on my side. I also see that there are one or two more copulas in your twincopulas that could me migrated to here. Also statistics such as Blomqvist \beta & others could be migrated too if you want, with potentail restrictions to $d=2$ by the type system directly.

Once all of that is done, I could help you design dynamic stuff on top of the class system that is here if you want / need !

Let's stay in touch.

++
Oskar

Santymax98 · 2024-07-29T17:55:12Z

Yes, first I wanted to leave extreme value domes in good condition, then we can see the other copulas, in general they have the same structure, I think they have good implementations El El lun, 29 jul. 2024 a la(s) 12:06, Oskar Laverny < ***@***.***> escribió:

…

Yeah take your time, there is no rush on my side. I also see that there are one or two more copulas in your twincopulas version that could me migrated to here. Once all of that is done, I could help you design dynamic stuff on top of the class system that is here if you want / need ! Let's stay in touch. ++ Oskar — Reply to this email directly, view it on GitHub <#208 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/A7PTWNUMP224G2WV34PBBW3ZOZZC7AVCNFSM6AAAAABLPBR3F6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDENJWGQ3DAMZUG4> . You are receiving this because you were mentioned.Message ID: ***@***.***>

codecov · 2024-07-29T23:47:19Z

Codecov Report

Attention: Patch coverage is 81.00264% with 72 lines in your changes missing coverage. Please review.

Project coverage is 86.32%. Comparing base (b9bc7e4) to head (42568e4).
Report is 67 commits behind head on main.

Files	Patch %	Lines
src/ExtremeValueCopula.jl	59.72%	29 Missing ⚠️
src/ExtremeValueCopulas/tEVCopula.jl	84.37%	15 Missing ⚠️
src/ExtremeValueCopulas/BC2Copula.jl	66.66%	10 Missing ⚠️
src/ExtremeValueCopulas/AsymMixedCopula.jl	77.77%	4 Missing ⚠️
src/UnivariateDistribution/ExtremeDist.jl	84.00%	4 Missing ⚠️
src/ExtremeValueCopulas/AsymGalambosCopula.jl	85.00%	3 Missing ⚠️
src/ExtremeValueCopulas/AsymLogCopula.jl	76.92%	3 Missing ⚠️
src/ExtremeValueCopulas/CuadrasAugeCopula.jl	86.95%	3 Missing ⚠️
src/ExtremeValueCopulas/MOCopula.jl	96.29%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #208      +/-   ##
==========================================
+ Coverage   83.42%   86.32%   +2.90%     
==========================================
  Files          29       44      +15     
  Lines         748     1170     +422     
==========================================
+ Hits          624     1010     +386     
- Misses        124      160      +36

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

Santymax98 · 2024-07-29T23:59:30Z

Hello Oskar, I added the CDF directly, it appears that all the tests passed... would I need to start working with the documentation? In relation to Blomqvist \beta and giny´s coefficient \gamma, maybe we could do it in another PR?

lrnv · 2024-07-30T07:01:35Z

Yes beta and gamma would go in another PR that makes sense.

On this one you can correct the docs and we:ll be alright.

GG for MOCopula !

lrnv · 2024-07-31T07:12:37Z

II write it here as i think about it now: you could add up (in this PR) a line in the comparison table on the readme about bivariate extreme value copulas

Santymax98 · 2024-07-31T13:21:27Z

I had the same idea 🤣 El El mié, 31 jul. 2024 a la(s) 2:12, Oskar Laverny < ***@***.***> escribió:

…

II write it here as i think about it now: you could add up (in this PR) a line in the comparison table on the readme about bivariate extreme value copulas — Reply to this email directly, view it on GitHub <#208 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/A7PTWNXQBTTXA2WIMJ2BEMTZPCE7XAVCNFSM6AAAAABLPBR3F6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDENJZHAZTCOBVHA> . You are receiving this because you were mentioned.Message ID: ***@***.***>

modified: docs/src/assets/references.bib modified: docs/src/extremevalue/generalities.md modified: src/ExtremeValueCopula.jl

lrnv · 2024-08-01T08:12:26Z

The erros "Invalid sequence" seems to mean that you did not format the math correctly in the docstring : take a look at other docstrings (e.g. archimedeans) to see how it should be done.

lrnv · 2024-08-01T08:17:16Z

The output on Julia 1.10 is way better than on julia 1.6, it gives:

ERROR: LoadError: ParseError:
# Error @ /home/runner/work/Copulas.jl/Copulas.jl/src/ExtremeValueCopula.jl:26:118

In this way, in order to define a bivariate copula of extreme values, it is only necessary to introduce the function \( A\).
#                                                                                                                    └┘ ── invalid escape sequence
Stacktrace:

Santymax98 · 2024-08-02T13:24:42Z

@lrnv Do you think it's ready? Or do we need to add something else?

lrnv · 2024-08-02T18:46:55Z

I will review it tomorrow before merging but I think it's ok like that

lrnv · 2024-08-03T21:43:19Z

@Santymax98 see #210 there is an issue in the docs

Add examples of new copulas to the test

6f0bb6c

Santymax98 and others added 5 commits July 25, 2024 17:20

modified: Project.toml

ac91090

modified: src/Copulas.jl modified: src/ExtremeValueCopulas/tEVCopula.jl modified: src/UnivariateDistribution/ExtremeDist.jl

Merge branch 'extreme_value' of https://github.com/Santymax98/Copulas.jl

45ce311

into extreme_value

up tests

c260ee3

Merge branch 'extreme_value' of https://github.com/santymax98/copulas.jl

cbeef59

into pr/Santymax98/208

temporarily remove the KS test.

c377028

fix domainerrors

10ad15f

Santymax98 and others added 2 commits July 25, 2024 18:30

modified: src/ExtremeValue.jl

6b09602

modified: src/ExtremeValueCopulas/LogCopula.jl

add output of the name of the failling copula

94c982d

include new docs in make.jl

edd9bba

Santymax98 added 2 commits July 29, 2024 18:30

modified: src/ExtremeValueCopulas/MOCopula.jl

80282e8

modified: src/ExtremeValueCopula.jl retype A

9658bb3

Santymax98 added 8 commits July 29, 2024 20:16

Add: Pickands function test in test/Extreme_value_test.jl

f2651b1

modified: test/Extreme_value_test.jl

e299b3f

modified: test/Extreme_value_test.jl

3cc5fbf

modified: test/Extreme_value_test.jl

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modified: test/Extreme_value_test.jl

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modified: test/Extreme_value_test.jl

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modified: test/Extreme_value_test.jl

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modified: test/Extreme_value_test.jl

b83ec8e

Santymax98 added 4 commits August 1, 2024 06:42

modified: README.md

09e7a64

modified: docs/src/assets/references.bib modified: docs/src/extremevalue/generalities.md modified: src/ExtremeValueCopula.jl

modified: src/ExtremeValueCopula.jl

c18fc63

modified: src/ExtremeValueCopula.jl

e1caed0

modified: src/ExtremeValueCopula.jl

62f6676

lrnv approved these changes Aug 1, 2024

View reviewed changes

modified: src/ExtremeValueCopula.jl

42568e4

lrnv merged commit f8eb5aa into lrnv:main Aug 3, 2024
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add Bivariate Extreme Value Copulas #208

add Bivariate Extreme Value Copulas #208

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add Bivariate Extreme Value Copulas #208

add Bivariate Extreme Value Copulas #208

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