[R-br] Erro em solve.default(v$varcov, xmat) GeoR likfit
Rodrigo Sant'Ana
rodrigo.gringo em gmail.com
Terça Setembro 18 17:24:31 BRT 2012
Prezado Prof. Paulo,
novamente, obrigado, realmente eu estava fazendo esta confusão. Sem
sombra de dúvida, era exatamente isso que eu estava acreditando.
Quanto a distância dos pontos, eles podem ser relativamente próximos
sim, se comparados com a máxima distância entre dois pontos na área de
estudo. Pois pontos vizinhos estão, aproximadamente, equidistantes 1
km um dos outros, e a máxima distância entre pontos chega a quase 15
graus de latitude. É uma área de estudo é consideravelmente grande.
Mas este não seria um problema para aplicação do método, certo Prof.?
abs
_____________________________
Rodrigo Sant'Ana
Oceanógrafo
Em 18 de setembro de 2012 16:34, Paulo Justiniano
<paulojus em leg.ufpr.br> escreveu:
> Caro Rodrigo
>
> O fato de com matern Kappa > 4 dar problema quase certamente está ligado com
> o provavel fato de que voce tem localizacoes muito proximas comparadas com a
> maior distancia entrew pontos na área
>
> quant a escolha do GaUSSIANO VOCE ESTÁ FAZENDO UMA CONFUSÃO:
> a distribuicao normal multivariada da resposta nao tem NADA a ver
> com o modelo gaussiano de funcao de correlacao
>
> é uma simples coincidencia de nomes pelo fato da segunda ter uma expressao
> que coincide com o nucleo de uma distribuicao normal.
>
> Mas distribuicao a resposta e funcao de correlacao sao coisas distintas
> (da mesma forma que o modelo exponencial nao tem NADAa ver com a
> distribuicaoi de resposta que pode perfeitamente ser normal
>
>
>
> On Tue, 18 Sep 2012, Rodrigo Sant'Ana wrote:
>
>> Prof. Paulo,
>>
>> muito obrigado, muito obrigado mesmo.. Mesmo sem reproduzir o
>> exemplo, o Sr. atingiu o nervo da questão.
>> Adicionei, um nugget maior que zero a fim de testar o procedimento, e
>> rodou sem apresentar o Erro anterior.
>> Utilizei também, conforme sua orientação, um modelo Matérn com kappa
>> 4, pois com valores superiores o problema anterior se repetiu. e o
>> mesmo rodou perfeitamente.
>>
>> Quanto ao fato da insistência em rodar um modelo gaussiano vem da
>> origem destes dados. Eles foram simulados por uma distribuição normal
>> multivariada, buscando-se assemelhar a distribuição de uma espécie de
>> peixe em uma área conhecida, de onde posteriormente foram tiradas
>> amostras aleatórias variando o "n" e o desenho amostral empregado. O
>> intuito final é verificar as diferenças entre os distintos
>> procedimentos amostrais em estimar a biomassa total do recurso em
>> relação ao total simulado pela distribuição normal multivariada, sob o
>> enfoque de métodos distintos de expansão/estimação. De todo modo,
>> outros modelos também foram ajustados também (esférico, matern,
>> exponencial) para comparação com o modelo Gaussiano, o qual era
>> esperado o melhor ajuste.
>>
>> Novamente, muito obrigado por seus ensinamentos Prof. Paulo. Muito
>> obrigado mesmo!
>>
>> _______________
>> Rodrigo Sant'Ana
>> Oceanógrafo
>>
>>
>> Em 17 de setembro de 2012 17:55, Paulo Justiniano
>> <paulojus em leg.ufpr.br> escreveu:
>>>
>>> Não tentei reproduzir seu exemplo mas suas informações dão uma pista do
>>> problema
>>>
>>> O modelo Gaussiano de função de correlação é muito suave na origem.
>>> A consequyencioa disto é q de que facilmente pode-se gerar
>>> inderteminações
>>> numéricas com este modelo.
>>>
>>> Isto ocorre quando o parametro de nugget está em zero aliado a
>>> coordenadas
>>> muito proximas de pontos. A suavidade da função acaba gerando
>>> linhas/colunas
>>> na matrix de correlação não distinguiveis nomericamente e daí a
>>> singularidade (numérica)
>>>
>>> Este fato é bem conhecido e por isto não se recomenda o uso do Gaussiano,
>>> ou
>>> se recomenda combinado com algum nugget (mas ai somente para predicao)
>>>
>>> Se quiser obter algo semelhante ao gaussiano (por que usar este modelo tb
>>> é
>>> uma pergunta relevante - o fato de que "todo mundo usa" nao é resposta
>>> válida) sugiro usar o Matern com um valor mais elevado de kappa (4.5 ou
>>> superior.
>>>
>>>
>>>
>>> On Mon, 17 Sep 2012, Rodrigo Sant'Ana wrote:
>>>
>>>> Pessoal,
>>>>
>>>> no email enviando anteriormente existiam alguns erros no CMR, bem como
>>>> a identificação do problema estava muito vaga. Seguem as correções no
>>>> mesmo para que seja possível reproduzi-lo. Desculpem-me pelos erros
>>>> anteriores.
>>>>
>>>> Identificação do problema: Erro em solve.default(v$varcov, xmat) :
>>>> sistema é computacionalmente
>>>> singular: condição recíproca número = 6.36899e-20
>>>>
>>>> Função utilizada: geoR::likfit
>>>>
>>>> Dúvida: Busquei como solução, passar pelo argumento control da função
>>>> geoR::likfit algumas mundanças na optimização do modelo, tais como,
>>>> control = list(method = "CG"); Mas não obtive exito. Rodando outros
>>>> modelos
>>>> que não o Gaussiano para a mesma base de dados (ex: Exponencial,
>>>> Matern, Esférico) o problema não ocorre.
>>>> Teria como passar uma modificação para matrix svd?? Acho que é ai onde
>>>> esta ocorrendo o Erro, não?
>>>>
>>>> Código Minimo Reproduzível
>>>>
>>>> ## Carrega o pacote geoR
>>>> library(geoR)
>>>>
>>>> ## Entrada dos dados
>>>> dados.geo <- structure(list(coords = structure(c(-42.2064355778,
>>>> -42.3032008959,
>>>> -41.5452059035, -42.1580529187, -41.1420170777, -42.9724943467,
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>>>> -33.7195349641, -33.8615470282, -33.8699006791, -33.8866079807,
>>>> -33.9701444891), .Dim = c(200L, 2L)), data = c(70.347798763,
>>>> 76.2305279637, 56.7935202123, 91.2747172018, 36.6574714598,
>>>> 74.5676848522,
>>>> 80.45544927, 63.7985345319, 98.6062126882, 76.1440959745, 78.0342424622,
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>>>> 95.7125681057,
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>>>> 141.733992676,
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>>>> -41.8233586956522,
>>>> -41.9986114130435, -42.2535244565217, -42.4447092391304,
>>>> -42.5243695652173, -42.7792826086957, -42.9704673913043,
>>>> -43.3050407608695, -43.4802934782608, -43.6396141304347,
>>>> -43.8626630434782, -44.1016440217391, -44.2928288043478,
>>>> -44.4840135869565, -44.627402173913, -44.7548586956522,
>>>> -44.8982472826086,
>>>> -45.0097717391304, -45.1372282608695, -45.2646847826086,
>>>> -45.3602771739131, -45.4558695652173, -45.5992581521739,
>>>> -45.5514619565217, -45.5992581521739, -45.7426467391305,
>>>> -45.9816277173912, -46.1728125, -46.3162010869565,
>>>> -46.5073858695652,
>>>> -46.7145027173913, -46.8419592391304, -46.9375516304348,
>>>> -46.9375516304348, -47.0331440217391, -47.0331440217391,
>>>> -47.0012798913043, -46.9056875, -46.8578913043478,
>>>> -46.8419592391304,
>>>> -46.9056875, -46.985347826087, -47.0650081521739, -47.2243288043478,
>>>> -47.4155135869565, -47.6066983695652, -47.7341548913043,
>>>> -47.7819510869565, -47.8297472826087, -47.7819510869565,
>>>> -47.8138152173913, -47.8616114130435, -47.9253396739131,
>>>> -47.9253396739131, -48.0687282608695, -48.291777173913,
>>>> -48.4829619565218,
>>>> -48.7219429347826, -48.8175353260869, -48.9927880434782,
>>>> -49.1680407608695, -49.3114293478261, -49.5344782608695,
>>>> -49.6778668478261, -49.7734592391304, -49.9487119565217,
>>>> -50.0921005434783, -50.1398967391304, -50.2673532608696,
>>>> -50.2832853260869, -50.2832853260869, -50.3151494565217,
>>>> -50.3629456521739, -50.5541304347826, -50.6815869565217,
>>>> -50.8727717391304, -51.0002282608695, -51.2073451086957,
>>>> -51.3029375, -51.3348016304348, -51.4463260869564,
>>>> -51.3507336956521,
>>>> -51.4941222826087, -51.5737826086956, -51.6215788043478,
>>>> -51.7808994565218, -51.9083559782608, -52.0676766304347),
>>>> coords.x2 = c(-34.511214673913, -34.3200298913043, -34.2244375,
>>>> -34.1607092391304, -34.0651168478261, -33.9217282608695,
>>>> -33.7464755434783, -33.6349510869565, -33.5074945652174,
>>>> -33.3800380434783, -33.2685135869565, -33.0932608695652,
>>>> -33.1410570652174, -33.0613967391304, -32.9020760869565,
>>>> -32.7427554347826, -32.5675027173913, -32.471910326087,
>>>> -32.2647934782608, -32.0736086956522, -31.8824239130434,
>>>> -31.7390353260869, -31.5956467391304, -31.372597826087,
>>>> -31.1495489130434, -30.9583641304347, -30.7193831521739,
>>>> -30.5600625, -30.4644701086957, -30.2732853260869,
>>>> -30.0980326086956,
>>>> -29.9865081521739, -29.7953233695652, -29.6041385869565,
>>>> -29.4288858695652, -29.3332934782608, -29.1739728260869,
>>>> -29.0305842391305, -28.8393994565217, -28.648214673913,
>>>> -28.4092336956522, -28.281777173913, -28.1224565217391,
>>>> -28.0268641304347, -27.8834755434783, -27.7082228260869,
>>>> -27.5966983695652, -27.3895815217391, -27.2302608695651,
>>>> -27.0709402173912, -26.9275516304348, -26.7363668478261,
>>>> -26.6248423913044, -26.5133179347825, -26.3858614130435,
>>>> -26.1946766304347, -25.9875597826087, -25.8441711956521,
>>>> -25.7007826086956, -25.5573940217391, -25.3662092391304,
>>>> -25.2387527173913, -25.1272282608695, -24.9997717391304,
>>>> -24.8563831521739, -24.6651983695652, -24.4580815217391,
>>>> -24.250964673913, -24.1394402173913, -24.0597798913043,
>>>> -23.8845271739131, -23.7570706521739, -23.6614782608695,
>>>> -23.5340217391304, -23.4384293478261, -23.3428369565217,
>>>> -23.2950407608695, -23.2153804347826, -23.1675842391305,
>>>> -23.1038559782609, -23.0560597826087, -23.0560597826087,
>>>> -23.1038559782609, -23.2153804347826, -23.2153804347826,
>>>> -23.2153804347826, -23.1994483695652, -23.3109728260869,
>>>> -23.4702934782608, -23.5658858695652, -23.6774103260869,
>>>> -23.8048668478261, -23.8207989130435, -23.8207989130435,
>>>> -23.7730027173913, -23.7730027173913, -23.7730027173913,
>>>> -23.8685951086956, -23.9641875, -24.0597798913043,
>>>> -24.2031684782609,
>>>> -24.2828288043478, -24.3465570652173, -24.4262173913044,
>>>> -24.5377418478261, -24.7129945652174, -24.8404510869565,
>>>> -24.9519755434783, -25.143160326087, -25.3343451086956,
>>>> -25.509597826087, -25.7007826086956, -25.796375,
>>>> -25.8760353260869,
>>>> -25.8441711956521, -25.9716277173912, -26.0353559782608,
>>>> -26.1309483695651, -26.1787445652174, -26.5133179347825,
>>>> -26.8000951086956, -27.0072119565218, -27.1346684782609,
>>>> -27.182464673913, -27.2461929347825, -27.3417853260869,
>>>> -27.4214456521739, -27.4851739130435, -27.5807663043478,
>>>> -27.7560190217391, -27.915339673913, -28.0905923913044,
>>>> -28.2499130434783, -28.3933016304348, -28.5844864130434,
>>>> -28.7119429347826, -28.7119429347826, -28.807535326087,
>>>> -28.9031277173913, -29.0943124999999, -29.3014293478261,
>>>> -29.4766820652174, -29.7475271739131, -29.9865081521739,
>>>> -30.2254891304348, -30.3688777173912, -30.5122663043478,
>>>> -30.5122663043478, -30.6078586956521, -30.6875190217391,
>>>> -30.7353152173913, -30.7353152173913, -30.7831114130435,
>>>> -30.9105679347826, -31.0380244565217, -31.2292092391304,
>>>> -31.4044619565217, -31.6115788043478, -31.8346277173912,
>>>> -32.1054728260869, -32.3125896739131, -32.4878423913044,
>>>> -32.6949592391304, -32.8861440217391, -33.125125,
>>>> -33.3003777173913,
>>>> -33.4915624999999, -33.6030869565217, -33.6827472826087,
>>>> -33.6986793478261, -33.7942717391304, -33.7942717391304,
>>>> -33.9057961956522, -33.9057961956522, -34.0173206521739,
>>>> -34.0969809782609, -34.1607092391304, -34.2881657608695,
>>>> -34.4474864130434, -34.4793505434782, -34.511214673913
>>>> )), .Names = c("coords.x1", "coords.x2"), class =
>>>> "data.frame", row.names = c(NA,
>>>> -181L))), .Names = c("coords", "data", "borders"), class =
>>>> "geodata")
>>>>
>>>>
>>>> ## Matrix com os chutes iniciais de Sigma e Phi
>>>> ini.fit <- expand.grid((2000:5000), (0:12)/12)
>>>>
>>>> ## Modelo
>>>> mod.gau <- likfit(dados.geo, ini.cov.pars = ini.fit, cov.model =
>>>> "gau", trend = "cte", fix.nugget = FALSE,
>>>> fix.lambda = FALSE, lik.method = "ML")
>>>>
>>>> ### Identificação do problema resultante!
>>>>
>>>> kappa not used for the gaussian correlation function
>>>> likfit: searching for best initial value ... selected values:
>>>>
>>>> sigmasq phi tausq kappa lambda psiR
>>>> initial.value "2952.00" " 0.83" " 0.00" " 0.50" " 1.00" "
>>>> 1.00"
>>>> status "est" "est" "est" "fix" "est" "fix"
>>>> psiA
>>>> initial.value " 0.00"
>>>> status "fix"
>>>> likelihood value: -319.704123974414
>>>> ---------------------------------------------------------------
>>>> likfit: likelihood maximisation using the function optim.
>>>> likfit: Use control() to pass additional
>>>> arguments for the maximisation function.
>>>> For further details see documentation for optim.
>>>> likfit: It is highly advisable to run this function several
>>>> times with different initial values for the parameters.
>>>> likfit: WARNING: This step can be time demanding!
>>>> ---------------------------------------------------------------
>>>> trying another decomposition (svd)
>>>> Erro em solve.default(v$varcov, xmat) :
>>>> sistema é computacionalmente singular: condição recíproca número =
>>>> 6.36899e-20
>>>>
>>>>
>>>> _______________
>>>> Rodrigo Sant'Ana
>>>> Oceanógrafo
>>>>
>>>>
>>>> Em 16 de setembro de 2012 18:05, Rodrigo Sant'Ana
>>>> <rodrigo.gringo em gmail.com> escreveu:
>>>>>
>>>>>
>>>>> Caros,
>>>>>
>>>>> estou tentando ajustar um modelo gaussiano aos de biomassa de peixe
>>>>> (kg), e estou caindo em um problema que não consigo identificar o
>>>>> motivo!
>>>>> Abaixo segue o CMR, bem como o Erro resultante do procedimento.
>>>>>
>>>>> Obrigado.
>>>>>
>>>>> dados <- structure(list(coords = structure(c(-42.2064355778,
>>>>> -42.3032008959,
>>>>> -41.5452059035, -42.1580529187, -41.1420170777, -42.9724943467,
>>>>> -41.7306727634, -43.2224714187, -42.601560627, -43.0773234414,
>>>>> -43.0692596649, -42.61768818, -42.6499432861, -42.7708999338,
>>>>> -42.6338157331, -43.0128132293, -42.2951371194, -42.319328449,
>>>>> -41.7387365399, -43.0692596649, -42.3032008959, -42.3596473316,
>>>>> -42.4402850967, -43.4643847142, -43.6579153505, -43.7304893392,
>>>>> -43.8272546573, -42.7547723808, -44.2143159301, -43.7224255627,
>>>>> -43.117642324, -43.4724484907, -44.3272088013, -43.7466168922,
>>>>> -43.4160020551, -44.149805718, -43.8595097634, -44.6175047559,
>>>>> -44.1981883771, -44.2143159301, -44.6497598619, -45.0690762407,
>>>>> -44.9884384756, -44.5368669907, -44.8836093809, -44.5852496498,
>>>>> -44.7707165096, -45.1497140059, -45.5448390551, -44.948119593,
>>>>> -45.1497140059, -45.6254768203, -46.1334947407, -45.0610124642,
>>>>> -45.4722650665, -45.6254768203, -45.2787344301, -45.5932217142,
>>>>> -45.1900328884, -45.9480278809, -45.9641554339, -46.2141325059,
>>>>> -45.5125839491, -46.4963646839, -46.6253851082, -45.4077548544,
>>>>> -45.6335405968, -46.6495764377, -46.6737677673, -46.6253851082,
>>>>> -45.6496681498, -46.1415585173, -45.9641554339, -45.746433468,
>>>>> -46.5528111195, -45.99641054, -47.0688928165, -46.0447931991,
>>>>> -46.1334947407, -46.4318544718, -46.3834718127, -46.52861979,
>>>>> -46.6737677673, -47.4478903128, -46.4318544718, -47.2624234529,
>>>>> -47.4398265362, -47.310806112, -46.9882550514, -46.3270253771,
>>>>> -46.810851968, -46.8592346271, -46.8269795211, -47.6817398317,
>>>>> -47.1898494643, -47.4962729718, -47.4801454188, -46.9721274983,
>>>>> -47.6978673847, -47.0043826044, -47.6575485022, -47.7059311612,
>>>>> -47.8913980211, -47.4156352067, -47.843015362, -47.6736760552,
>>>>> -47.4720816423, -47.1575943582, -47.06082904, -47.2221045703,
>>>>> -47.6252933961, -47.7381862673, -47.3188698885, -47.1253392521,
>>>>> -47.3027423355, -47.1092116991, -47.8026964794, -47.9317169037,
>>>>> -47.6333571726, -47.5365918544, -47.576910737, -47.0527652635,
>>>>> -47.3591887711, -46.9801912749, -47.7220587143, -47.2059770173,
>>>>> -47.5688469605, -48.0849286575, -47.6575485022, -47.9800995628,
>>>>> -47.560783184, -48.1978215287, -47.9559082332, -48.4800537067,
>>>>> -48.6332654605, -48.6493930135, -48.5445639188, -48.4961812598,
>>>>> -48.3671608355, -48.2381404113, -47.9962271158, -48.8106685439,
>>>>> -48.7139032257, -47.9155893506, -47.9317169037, -48.5606914719,
>>>>> -48.4074797181, -48.9477527446, -47.9720357863, -48.5203725893,
>>>>> -48.7461583317, -48.0607373279, -49.0848369454, -48.8671149795,
>>>>> -49.0929007219, -48.3913521651, -48.9638802976, -49.1977298166,
>>>>> -48.5606914719, -49.2461124757, -48.3268419529, -48.7300307787,
>>>>> -48.1736301991, -49.407388006, -48.4477986007, -49.0525818393,
>>>>> -48.5284363658, -49.7138115136, -48.7622858848, -49.5041533242,
>>>>> -49.6815564075, -49.0929007219, -49.3590053469, -49.3509415704,
>>>>> -49.6654288545, -49.8831508204, -49.8428319378, -49.8347681613,
>>>>> -49.9637885855, -49.8105768318, -50.1492554454, -49.8670232674,
>>>>> -50.0363625742, -50.455678953, -50.3669774113, -50.3024671992,
>>>>> -50.4072962939, -50.3589136348, -50.5121253886, -50.6492095894,
>>>>> -50.3831049643, -50.9153142144, -50.6814646954, -51.1491637333,
>>>>> -50.7540386841, -51.4959061235, -51.4797785704, -51.3991408053,
>>>>> -51.6007352182, -51.5281612295, -23.1939349125, -23.2357031667,
>>>>> -23.26911777, -23.3359469767, -23.36936158, -23.3777152309,
>>>>> -23.4027761834,
>>>>> -23.4111298342, -23.4194834851, -23.4278371359, -23.4361907867,
>>>>> -23.4528980884, -23.4612517392, -23.4779590409, -23.5280809459,
>>>>> -23.5280809459, -23.5614955492, -23.5614955492, -23.5698492001,
>>>>> -23.5782028509, -23.6366784067, -23.7118612643, -23.7619831693,
>>>>> -23.7619831693, -23.7619831693, -23.8121050743, -23.8288123759,
>>>>> -23.8538733284, -23.8622269793, -23.8705806301, -23.9039952335,
>>>>> -23.9039952335, -23.9541171385, -24.079421901, -24.1378974568,
>>>>> -24.1462511077, -24.2715558702, -24.2966168227, -24.3634460294,
>>>>> -24.3885069819, -24.5472263477, -24.6808847611, -24.7393603169,
>>>>> -24.7477139677, -24.7727749202, -24.7811285711, -24.8479577778,
>>>>> -24.9649088894, -25.1152746045, -25.1570428586, -25.3241158753,
>>>>> -25.3241158753, -25.340823177, -25.3658841295, -25.390945082,
>>>>> -25.3992987328, -25.4160060345, -25.4577742887, -25.4744815904,
>>>>> -25.5078961937, -25.5078961937, -25.5078961937, -25.5747254004,
>>>>> -25.6499082579, -25.6499082579, -25.6666155595, -25.6666155595,
>>>>> -25.6833228612, -25.7334447662, -25.8169812746, -25.8503958779,
>>>>> -25.8503958779, -25.8587495287, -25.8671031796, -25.9339323863,
>>>>> -25.9506396879, -26.0675907996, -26.0759444504, -26.0759444504,
>>>>> -26.2263101655, -26.2430174671, -26.301493023, -26.4435050872,
>>>>> -26.5604561988, -26.5855171513, -26.6439927072, -26.7191755647,
>>>>> -26.7609438189, -26.8611876289, -26.9614314389, -26.9781387406,
>>>>> -27.0199069947, -27.0616752489, -27.0700288998, -27.0867362014,
>>>>> -27.0950898523, -27.1452117573, -27.1702727098, -27.2621628689,
>>>>> -27.362406679, -27.4542968381, -27.5211260448, -27.5294796957,
>>>>> -27.5796016007, -27.5963089023, -27.613016204, -27.6213698548,
>>>>> -27.6297235057, -27.6714917598, -27.6714917598, -27.8051501732,
>>>>> -27.8719793799, -28.0223450949, -28.0641133491, -28.0975279524,
>>>>> -28.2228327149, -28.2980155724, -28.3147228741, -28.3230765249,
>>>>> -28.3899057316, -28.3982593824, -28.4567349383, -28.4817958908,
>>>>> -28.5319177958, -28.5653323991, -28.6572225583, -28.6572225583,
>>>>> -28.6822835108, -28.77417367, -28.7825273208, -28.8493565275,
>>>>> -28.924539385, -28.9579539884, -28.9579539884, -29.1918562117,
>>>>> -29.3004536726, -29.3255146251, -29.3422219267, -29.4424657368,
>>>>> -29.4675266893, -29.5092949434, -29.5761241501, -29.5928314518,
>>>>> -29.6095387535, -29.6513070076, -29.684721611, -29.7264898651,
>>>>> -29.7766117701, -29.8267336752, -29.8434409768, -29.8434409768,
>>>>> -30.035574946, -30.035574946, -30.0439285969, -30.0689895494,
>>>>> -30.2110016135, -30.2444162169, -30.3195990744, -30.4365501861,
>>>>> -30.4449038369, -30.4950257419, -30.5284403453, -30.5451476469,
>>>>> -30.5702085994, -30.5952695519, -30.6119768536, -30.6286841553,
>>>>> -30.6537451078, -30.6704524094, -30.7205743145, -30.7289279653,
>>>>> -30.845879077, -30.8792936803, -31.0630739987, -31.0714276495,
>>>>> -31.1299032053, -31.3303908254, -31.4306346354, -31.4389882862,
>>>>> -31.5141711437, -31.6561832079, -31.6812441604, -31.6812441604,
>>>>> -32.5834384506, -32.6753286097, -32.7672187689, -32.8256943248,
>>>>> -32.9175844839, -33.0763038498, -33.1264257548, -33.2350232157,
>>>>> -33.2767914698, -33.3853889307, -33.3853889307, -33.5608155982,
>>>>> -33.7195349641, -33.8615470282, -33.8699006791, -33.8866079807,
>>>>> -33.9701444891), .Dim = c(200L, 2L)), data = c(70.347798763,
>>>>> 76.2305279637, 56.7935202123, 91.2747172018, 36.6574714598,
>>>>> 74.5676848522,
>>>>> 80.45544927, 63.7985345319, 98.6062126882, 76.1440959745,
>>>>> 78.0342424622,
>>>>> 103.211817252, 103.469894054, 101.543807018, 113.430501289,
>>>>> 96.7287932817,
>>>>> 119.081813263, 119.357653249, 91.6231191698, 101.038405309,
>>>>> 123.946425703,
>>>>> 127.264845138, 129.378943162, 101.547939554, 90.634442506,
>>>>> 95.7125681057,
>>>>> 94.798698159, 136.088211184, 83.1631121458, 105.907150692,
>>>>> 134.683969664,
>>>>> 120.236176625, 93.2955838471, 135.734205354, 134.793068333,
>>>>> 146.056344048,
>>>>> 156.071027198, 118.33813258, 176.165459485, 178.101033469,
>>>>> 141.733992676,
>>>>> 68.1513901758, 85.906096787, 160.683155231, 106.672886988,
>>>>> 153.732695652,
>>>>> 126.282924957, 71.171101282, 46.3063932604, 94.8066154966,
>>>>> 79.6077933159,
>>>>> 66.3022759053, 53.8001871156, 81.8971879578, 75.2725941278,
>>>>> 76.3895591688,
>>>>> 78.1481792228, 84.0088538824, 79.2339837253, 95.3285594814,
>>>>> 94.9048569376,
>>>>> 79.7371402431, 94.8361107261, 75.6734008995, 56.8583003566,
>>>>> 93.9377590667,
>>>>> 114.925013457, 58.7902731855, 63.3651704313, 87.7623028428,
>>>>> 138.243923048,
>>>>> 174.14679455, 176.924595279, 155.265108276, 130.599056347,
>>>>> 197.328254597,
>>>>> 43.1264520732, 221.751423068, 226.374023855, 231.22155796,
>>>>> 242.436720324,
>>>>> 225.68515641, 211.182339909, 30.7901884494, 268.635407904,
>>>>> 66.9770777548,
>>>>> 43.4651532814, 69.6985834637, 162.069565781, 201.17261197,
>>>>> 206.563852105,
>>>>> 197.412358817, 200.569088904, 36.5304326403, 134.230440546,
>>>>> 68.9447508778,
>>>>> 77.3092256209, 179.991789488, 46.7833022819, 178.837329648,
>>>>> 67.6041455343,
>>>>> 61.735642779, 30.9986850158, 136.367462528, 40.2420355711,
>>>>> 74.1549949452,
>>>>> 125.706398802, 182.134045089, 183.669620178, 179.176911697,
>>>>> 96.3292516587,
>>>>> 71.0485302772, 177.743449233, 187.3998893, 179.464856475,
>>>>> 177.962224878,
>>>>> 72.9460880655, 52.2011730864, 109.173183978, 129.8967523,
>>>>> 121.836259287,
>>>>> 147.025253713, 152.031441102, 124.646779658, 100.076387829,
>>>>> 133.011240036,
>>>>> 120.939828964, 64.3940362035, 114.996266127, 89.786038347,
>>>>> 118.008543994,
>>>>> 84.0282040216, 119.041263465, 44.0234944515, 41.8771712674,
>>>>> 48.2651512851,
>>>>> 73.4117997844, 87.9741710827, 142.802105252, 186.596945575,
>>>>> 228.955878351,
>>>>> 39.727571142, 59.5842097784, 237.196336949, 244.661132149,
>>>>> 111.885460631,
>>>>> 172.978503244, 31.9606458285, 262.185785391, 142.37968626,
>>>>> 71.9893685188,
>>>>> 261.41293353, 32.6187049615, 61.3911365603, 33.9234837497,
>>>>> 194.293576816,
>>>>> 59.9894516509, 40.4781868063, 136.131434893, 43.8955202545,
>>>>> 166.161274956,
>>>>> 101.623813429, 160.809302111, 39.3742142225, 134.084319986,
>>>>> 65.9772777256,
>>>>> 119.705366465, 27.1765413035, 90.2079815554, 41.3695883805,
>>>>> 32.9317985059,
>>>>> 61.9912390925, 53.1711001574, 53.8325000656, 52.2218112743,
>>>>> 49.1524441926,
>>>>> 62.6024730954, 67.1897383436, 66.0508521024, 69.425604381,
>>>>> 69.874832943,
>>>>> 73.9822629935, 75.6320803161, 98.9442750104, 108.632920447,
>>>>> 111.310932929,
>>>>> 117.076441302, 119.455819615, 125.059523339, 117.758307932,
>>>>> 117.561279774,
>>>>> 90.3341173828, 113.921889667, 67.6379513723, 99.9119129685,
>>>>> 58.2801014975,
>>>>> 63.4483498456, 66.4356707327, 57.6791519282, 62.3488331665),
>>>>> borders = structure(list(coords.x1 = c(-52.0676766304347,
>>>>> -52.0039483695653, -51.956152173913, -51.7968315217391,
>>>>> -51.6853070652174,
>>>>> -51.6853070652174, -51.5419184782609, -51.4144619565217,
>>>>> -51.2710733695652, -51.1914130434782, -51.0002282608695,
>>>>> -50.8090434782609, -50.7134510869565, -50.6178586956521,
>>>>> -50.5541304347826, -50.5541304347826, -50.5700624999999,
>>>>> -50.4744701086956, -50.4585380434783, -50.410741847826,
>>>>> -50.4426059782608,
>>>>> -50.4426059782608, -50.4585380434783, -50.3310815217391,
>>>>> -50.2195570652173, -50.0283722826087, -49.8531195652174,
>>>>> -49.6619347826086, -49.47075, -49.3751576086956, -49.2636331521738,
>>>>> -49.1202445652174, -48.9768559782608, -48.8971956521739,
>>>>> -48.8334673913043, -48.7060108695651, -48.6422826086957,
>>>>> -48.658214673913, -48.4670298913043, -48.3077092391304,
>>>>> -48.1643206521739,
>>>>> -48.0368641304347, -48.0687282608695, -48.0209320652174,
>>>>> -48.0368641304347, -47.9890679347826, -47.9253396739131,
>>>>> -47.8297472826087, -47.7341548913043, -47.7341548913043,
>>>>> -47.6066983695652, -47.4951739130435, -47.4633097826087,
>>>>> -47.4473777173913, -47.3039891304348, -47.2083967391304,
>>>>> -47.0331440217391, -46.9216195652173, -46.7304347826087,
>>>>> -46.5073858695652, -46.2524728260869, -45.9816277173912,
>>>>> -45.7426467391305, -45.4558695652173, -45.2965489130434,
>>>>> -45.1212961956522, -44.9619755434783, -44.8504510869565,
>>>>> -44.7070624999999, -44.5955380434783, -44.4202853260869,
>>>>> -44.0857119565217, -43.894527173913, -43.6555461956522,
>>>>> -43.3847010869565,
>>>>> -43.0341956521739, -42.795214673913, -42.6040298913043,
>>>>> -42.4128451086956,
>>>>> -42.221660326087, -42.0464076086956, -41.9348831521739,
>>>>> -41.7436983695652,
>>>>> -41.4728532608696, -41.2976005434782, -41.1542119565217,
>>>>> -41.0108233695652, -41.0426875, -41.1542119565217,
>>>>> -41.2816684782609,
>>>>> -41.329464673913, -41.4887853260869, -41.6640380434783,
>>>>> -41.8233586956522,
>>>>> -41.9986114130435, -42.2535244565217, -42.4447092391304,
>>>>> -42.5243695652173, -42.7792826086957, -42.9704673913043,
>>>>> -43.3050407608695, -43.4802934782608, -43.6396141304347,
>>>>> -43.8626630434782, -44.1016440217391, -44.2928288043478,
>>>>> -44.4840135869565, -44.627402173913, -44.7548586956522,
>>>>> -44.8982472826086,
>>>>> -45.0097717391304, -45.1372282608695, -45.2646847826086,
>>>>> -45.3602771739131, -45.4558695652173, -45.5992581521739,
>>>>> -45.5514619565217, -45.5992581521739, -45.7426467391305,
>>>>> -45.9816277173912, -46.1728125, -46.3162010869565,
>>>>> -46.5073858695652,
>>>>> -46.7145027173913, -46.8419592391304, -46.9375516304348,
>>>>> -46.9375516304348, -47.0331440217391, -47.0331440217391,
>>>>> -47.0012798913043, -46.9056875, -46.8578913043478,
>>>>> -46.8419592391304,
>>>>> -46.9056875, -46.985347826087, -47.0650081521739,
>>>>> -47.2243288043478,
>>>>> -47.4155135869565, -47.6066983695652, -47.7341548913043,
>>>>> -47.7819510869565, -47.8297472826087, -47.7819510869565,
>>>>> -47.8138152173913, -47.8616114130435, -47.9253396739131,
>>>>> -47.9253396739131, -48.0687282608695, -48.291777173913,
>>>>> -48.4829619565218,
>>>>> -48.7219429347826, -48.8175353260869, -48.9927880434782,
>>>>> -49.1680407608695, -49.3114293478261, -49.5344782608695,
>>>>> -49.6778668478261, -49.7734592391304, -49.9487119565217,
>>>>> -50.0921005434783, -50.1398967391304, -50.2673532608696,
>>>>> -50.2832853260869, -50.2832853260869, -50.3151494565217,
>>>>> -50.3629456521739, -50.5541304347826, -50.6815869565217,
>>>>> -50.8727717391304, -51.0002282608695, -51.2073451086957,
>>>>> -51.3029375, -51.3348016304348, -51.4463260869564,
>>>>> -51.3507336956521,
>>>>> -51.4941222826087, -51.5737826086956, -51.6215788043478,
>>>>> -51.7808994565218, -51.9083559782608, -52.0676766304347),
>>>>> coords.x2 = c(-34.511214673913, -34.3200298913043, -34.2244375,
>>>>> -34.1607092391304, -34.0651168478261, -33.9217282608695,
>>>>> -33.7464755434783, -33.6349510869565, -33.5074945652174,
>>>>> -33.3800380434783, -33.2685135869565, -33.0932608695652,
>>>>> -33.1410570652174, -33.0613967391304, -32.9020760869565,
>>>>> -32.7427554347826, -32.5675027173913, -32.471910326087,
>>>>> -32.2647934782608, -32.0736086956522, -31.8824239130434,
>>>>> -31.7390353260869, -31.5956467391304, -31.372597826087,
>>>>> -31.1495489130434, -30.9583641304347, -30.7193831521739,
>>>>> -30.5600625, -30.4644701086957, -30.2732853260869,
>>>>> -30.0980326086956,
>>>>> -29.9865081521739, -29.7953233695652, -29.6041385869565,
>>>>> -29.4288858695652, -29.3332934782608, -29.1739728260869,
>>>>> -29.0305842391305, -28.8393994565217, -28.648214673913,
>>>>> -28.4092336956522, -28.281777173913, -28.1224565217391,
>>>>> -28.0268641304347, -27.8834755434783, -27.7082228260869,
>>>>> -27.5966983695652, -27.3895815217391, -27.2302608695651,
>>>>> -27.0709402173912, -26.9275516304348, -26.7363668478261,
>>>>> -26.6248423913044, -26.5133179347825, -26.3858614130435,
>>>>> -26.1946766304347, -25.9875597826087, -25.8441711956521,
>>>>> -25.7007826086956, -25.5573940217391, -25.3662092391304,
>>>>> -25.2387527173913, -25.1272282608695, -24.9997717391304,
>>>>> -24.8563831521739, -24.6651983695652, -24.4580815217391,
>>>>> -24.250964673913, -24.1394402173913, -24.0597798913043,
>>>>> -23.8845271739131, -23.7570706521739, -23.6614782608695,
>>>>> -23.5340217391304, -23.4384293478261, -23.3428369565217,
>>>>> -23.2950407608695, -23.2153804347826, -23.1675842391305,
>>>>> -23.1038559782609, -23.0560597826087, -23.0560597826087,
>>>>> -23.1038559782609, -23.2153804347826, -23.2153804347826,
>>>>> -23.2153804347826, -23.1994483695652, -23.3109728260869,
>>>>> -23.4702934782608, -23.5658858695652, -23.6774103260869,
>>>>> -23.8048668478261, -23.8207989130435, -23.8207989130435,
>>>>> -23.7730027173913, -23.7730027173913, -23.7730027173913,
>>>>> -23.8685951086956, -23.9641875, -24.0597798913043,
>>>>> -24.2031684782609,
>>>>> -24.2828288043478, -24.3465570652173, -24.4262173913044,
>>>>> -24.5377418478261, -24.7129945652174, -24.8404510869565,
>>>>> -24.9519755434783, -25.143160326087, -25.3343451086956,
>>>>> -25.509597826087, -25.7007826086956, -25.796375,
>>>>> -25.8760353260869,
>>>>> -25.8441711956521, -25.9716277173912, -26.0353559782608,
>>>>> -26.1309483695651, -26.1787445652174, -26.5133179347825,
>>>>> -26.8000951086956, -27.0072119565218, -27.1346684782609,
>>>>> -27.182464673913, -27.2461929347825, -27.3417853260869,
>>>>> -27.4214456521739, -27.4851739130435, -27.5807663043478,
>>>>> -27.7560190217391, -27.915339673913, -28.0905923913044,
>>>>> -28.2499130434783, -28.3933016304348, -28.5844864130434,
>>>>> -28.7119429347826, -28.7119429347826, -28.807535326087,
>>>>> -28.9031277173913, -29.0943124999999, -29.3014293478261,
>>>>> -29.4766820652174, -29.7475271739131, -29.9865081521739,
>>>>> -30.2254891304348, -30.3688777173912, -30.5122663043478,
>>>>> -30.5122663043478, -30.6078586956521, -30.6875190217391,
>>>>> -30.7353152173913, -30.7353152173913, -30.7831114130435,
>>>>> -30.9105679347826, -31.0380244565217, -31.2292092391304,
>>>>> -31.4044619565217, -31.6115788043478, -31.8346277173912,
>>>>> -32.1054728260869, -32.3125896739131, -32.4878423913044,
>>>>> -32.6949592391304, -32.8861440217391, -33.125125,
>>>>> -33.3003777173913,
>>>>> -33.4915624999999, -33.6030869565217, -33.6827472826087,
>>>>> -33.6986793478261, -33.7942717391304, -33.7942717391304,
>>>>> -33.9057961956522, -33.9057961956522, -34.0173206521739,
>>>>> -34.0969809782609, -34.1607092391304, -34.2881657608695,
>>>>> -34.4474864130434, -34.4793505434782, -34.511214673913
>>>>> )), .Names = c("coords.x1", "coords.x2"), class =
>>>>> "data.frame", row.names = c(NA,
>>>>> -181L))), .Names = c("coords", "data", "borders"), class =
>>>>> "geodata")
>>>>>
>>>>>
>>>>> ini.fit <- ini.fit <- expand.grid((2000:5000), (0:12)/12)
>>>>>
>>>>> mod.gau <- likfit(dados.geo, ini.cov.pars = ini.fit, cov.model =
>>>>> "gau", trend = "cte", fix.nugget = FALSE,
>>>>> fix.lambda = FALSE, lik.method = "ML")
>>>>>
>>>>>
>>>>> kappa not used for the gaussian correlation function
>>>>> likfit: searching for best initial value ... selected values:
>>>>> sigmasq phi tausq kappa lambda psiR
>>>>> initial.value "2952.00" " 0.83" " 0.00" " 0.50" " 1.00" "
>>>>> 1.00"
>>>>> status "est" "est" "est" "fix" "est" "fix"
>>>>> psiA
>>>>> initial.value " 0.00"
>>>>> status "fix"
>>>>> likelihood value: -319.704123974414
>>>>> ---------------------------------------------------------------
>>>>> likfit: likelihood maximisation using the function optim.
>>>>> likfit: Use control() to pass additional
>>>>> arguments for the maximisation function.
>>>>> For further details see documentation for optim.
>>>>> likfit: It is highly advisable to run this function several
>>>>> times with different initial values for the parameters.
>>>>> likfit: WARNING: This step can be time demanding!
>>>>> ---------------------------------------------------------------
>>>>> trying another decomposition (svd)
>>>>> Erro em solve.default(v$varcov, xmat) :
>>>>> sistema é computacionalmente singular: condição recíproca número =
>>>>> 6.36899e-20
>>>>>
>>>>>
>>>>> _______________
>>>>> Rodrigo Sant'Ana
>>>>> Oceanógrafo
>>>>
>>>>
>>>> _______________________________________________
>>>> R-br mailing list
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>>>> Leia o guia de postagem (http://www.leg.ufpr.br/r-br-guia) e forneça
>>>> código mínimo reproduzível.
>>>
>>>
>>>
>>> _______________________________________________
>>> R-br mailing list
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>>> Leia o guia de postagem (http://www.leg.ufpr.br/r-br-guia) e forneça
>>> código
>>> mínimo reproduzível.
>>
>> _______________________________________________
>> R-br mailing list
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>> código mínimo reproduzível.
>
>
> _______________________________________________
> R-br mailing list
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> mínimo reproduzível.
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