Dezembro 2015 - R-br

Criar um spatial points e shapefile com coordenadas e seus atributos
by ASANTOS 18 Dez '15

18 Dez '15

Caros Listeiros, Estou tentando criar um spatial points e posteriormente um shapefile com quatro variáveis, longitude (long), latitude (lat), espécie(esp) e cobertura (cob). Quando faço um cbind() apenas das informações geográficas, tudo OK, mas quando tento inserir os atributos esp e cob, a função SpatialPoints() não funciona. Alguém com experiência poderia me dar uma luz? Segue CRM: #Pacotes require(shapefiles); require(sp) #Pontos e variáveis esp e cob long<-c(-54.8956314,-54.8986246,-54.8985713, -54.8987823,-54.898895,-54.8988127) lat<-c(-30.4011373,-30.4121832,-30.4121513, -30.4120925,-30.4122421,-30.4123977) esp<-c("a","a","b","a","b","b") cob<-c(74.3,56.2,96.3,66.3,21.6,55.2) final.pts<-cbind(long,lat,esp,cob) #Transforma em spatial points pts.sampling = SpatialPoints(final.pts, proj4string=CRS("+proj=longlat +datum=WGS84")) ANTcoor.df <- SpatialPointsDataFrame(pts.sampling, data.frame(id=1:length(pts.sampling))) #Salva em shapefile writeOGR(ANTcoor.df, getwd(), 'ANTcoorF', 'ESRI Shapefile') Obrigado, -- ====================================================================== Alexandre dos Santos Proteção Florestal IFMT - Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso Campus Cáceres Caixa Postal 244 Avenida dos Ramires, s/n Bairro: Distrito Industrial Cáceres - MT CEP: 78.200-000 Fone: (+55) 65 8132-8112 (TIM) (+55) 65 9686-6970 (VIVO) e-mails:alexandresantosbr@yahoo.com.br alexandre.santos(a)cas.ifmt.edu.br Lattes: http://lattes.cnpq.br/1360403201088680 ======================================================================

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[fora] Exemplo bem-humorado de regressão à média
by Leonardo Ferreira Fontenelle 17 Dez '15

17 Dez '15

Assim como nos anos anteriores, esta edição natalina do periódico médico britânico *The BMJ* trouxe alguns artigos originais inusitados e divertidos. Acredito que boa parte dos companheiros da lista de discussão estarão interessados neste artigo como uma ilustração do conceito de regressão à média: http://dx.doi.org/10.1136/bmj.h6304 Att, Leonardo Ferreira Fontenelle[1] Links: 1. http://lattes.cnpq.br/9234772336296638

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Meetup R São Paulo Users Group - 2016
by Luis Benites Sánchez 17 Dez '15

17 Dez '15

Caros, Para o 2016 temos previstos os seguintes Meetup futuros de R para o 2016. ######################################################### *Sexta-feira, 4 de Março de 2016 14:00* - R e Julia uma comparação Parte I - Criação de pacotes - Parte I *Sexta-feira, 18 de Março de 2016 14:00* - Birnbaum-Saunders SN com aplicações em R - R e Julia uma comparação Parte II *Sexta-feira, 8 de Abril de 2016 14:00* - Técnicas de amostragem com R - Uma introdução ao dados de contagem com R *Sexta-feira, 6 de Maio de 2016 14:00* - ggplot - Ajustando modelos semi-paramétricos log-simétricos com R *Sexta-feira, 3 de Junho de 2016 14:00* - Visualizações em R *Sexta-feira, 22 de Julho de 2016 14:00* - Modelos de regressão com dados censurados SMSN - Introdução a amostragem com R *Sexta-feira, 29 de Julho de 2016 14:00* - Uma introdução a programação em paralelo em R - R Markdown - Parte 2 ######################################################### As datas e horários podem variar. As atualizações estarão disponíveis no site do Meetup. As palestras serão transmitidas ao vivo pelo YouTube. Para poder participar, pode confirmar sua participação gratuitamente no site do Meetup :) Para mais informações: Site: www.meetup.com/pt/useR-SP Canal de YouTube: www.youtube.com/channel/UCb9PdJYYaElE6Uqb1KxhE8w e-mail: meetuprsp(a)gmail.com Um abraço, Luis Benites Sánchez Rocío Paola Maehara Organizadores do São Paulo R Users Group

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Re: [R-br] Matrix de contrastes em fatorial DBC com a função glht!
by Ivan Bezerra Allaman 17 Dez '15

17 Dez '15

Prezado Walmes! Como sempre, muito obrigado! A função apcMatrix é muitíssimo útil. Uma sugestão! Embora eu saiba que tu não gostes de letrinhas, talvez seria interessante criar alguma função semelhante a função "cld", já que a mesma só trabalha caso seja indicado no argumento "linfct" a função "mcp" com o nome do tratamento de interesse. Em casos mais gerais como foi neste exemplo, a função "cld" não trabalha. Abraços!

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Re: [R-br] manipulação arquivos
by Rafael Tieppo 16 Dez '15

16 Dez '15

Paulo, MUITO obrigado! Tenho que estudar e aprender a usar as funções de manipulações! Salvou o dia! Abrax On Wednesday, December 16, 2015 4:03 PM, Paulo Abreu <abreups(a)gmail.com> wrote: Rafael, Porque você não tenta primeiro fazer um “pré-processamento” desse arquivo para só depois ler com o R?Por exemplo, se você usar o 'grep' com uma expressão regular para isolar somente as linhas com dados, você salva isso num outro arquivo e depois lê esse outro arquivo com o R.Salvei esse exemplo de dados que você passou num arquivo chamado teste.txt e executei o seguinte comando: grep "^ 198" < teste.txt O resultado são todas as linhas que começam com um espaço em branco e depois têm os caracteres 198 Assim: 1983 001 1 0.0 13.8 1983 002 2 0.0 13.8 1983 003 3 0.0 13.7 1984 001 1 2.2 13.8 1984 002 2 54.8 13.8 1984 003 3 4.8 13.7 Se você fizer grep "^ 198" < teste.txt > resultado.txt O arquivo resultado.txt vai ter só as linhas de dados.Coloca um cabeçalho à mão e aí fica mais fácil de ler com o R.Ajuste a expressão regular para ficar mais adequada aos dados que você tem (sei que você passou só um pedaço dos dados). Espero que ajude. Paulo Abreu Em 16 de dez de 2015, à(s) 16:14, Rafael Tieppo <rafaeltieppo(a)yahoo.com.br> escreveu: Prezados, Por favor, Alguém poderia me indicar algum pacote ou algum método para ler várias Tabelas em um único arquivo ".txt", quando há texto no meio do arquivo. Creio que o símbolo "@" permita iniciar a captura dos dados, mas não tenho ideia de como criar uma lógica. Obrigado EXEMPLO do ARQUIVO: *RUN 1 : POT_S1 @YEAR DOY DAS PRED DAYLD 1983 001 1 0.0 13.8 1983 002 2 0.0 13.8 1983 003 3 0.0 13.7 *RUN 2 : POT_S1 @YEAR DOY DAS PRED DAYLD 1984 001 1 2.2 13.8 1984 002 2 54.8 13.8 1984 003 3 4.8 13.7 Rafael Tieppo State University of Mato Grosso - Department of Agricultural Engineering site: http://www2.unemat.br/rafaeltieppo blog: https://fuidebicicleta.wordpress.com"Evite o desperdício: antes de imprimir pense na sua responsabilidade com o ambiente". _______________________________________________ R-br mailing list R-br(a)listas.c3sl.ufpr.br https://listas.inf.ufpr.br/cgi-bin/mailman/listinfo/r-br Leia o guia de postagem (http://www.leg.ufpr.br/r-br-guia) e forneça código mínimo reproduzível.

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manipulação arquivos
by Rafael Tieppo 16 Dez '15

16 Dez '15

Prezados, Por favor, Alguém poderia me indicar algum pacote ou algum método para ler várias Tabelas em um único arquivo ".txt", quando há texto no meio do arquivo. Creio que o símbolo "@" permita iniciar a captura dos dados, mas não tenho ideia de como criar uma lógica. Obrigado EXEMPLO do ARQUIVO: *RUN 1 : POT_S1 @YEAR DOY DAS PRED DAYLD 1983 001 1 0.0 13.8 1983 002 2 0.0 13.8 1983 003 3 0.0 13.7 *RUN 2 : POT_S1 @YEAR DOY DAS PRED DAYLD 1984 001 1 2.2 13.8 1984 002 2 54.8 13.8 1984 003 3 4.8 13.7 Rafael Tieppo State University of Mato Grosso - Department of Agricultural Engineering site: http://www2.unemat.br/rafaeltieppo blog: https://fuidebicicleta.wordpress.com"Evite o desperdício: antes de imprimir pense na sua responsabilidade com o ambiente".

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Matrix de contrastes em fatorial DBC com a função glht!
by Ivan Bezerra Allaman 15 Dez '15

15 Dez '15

Prezados, bom dia! Tenho os seguintes dados: gnexpo <- structure(list(celula = structure(c(7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("cd14il10", "cd14il12", "cd14TGFb", "cd14TNFa", "cd4il10", "cd4il17", "cd4il4", "cd4il6", "cd4infg", "cd8il10", "cd8il17", "cd8il4", "cd8il6", "cd8infg"), class = "factor"), tratamento = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 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44L, 44L, 44L, 44L, 44L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L), .Label = c("cd14il10sangue", "cd14il12sangue", "cd14TGFbsangue", "cd14TNFasangue", "cd4il10sangue", "cd4il17sangue", "cd4il4sangue", "cd4il6sangue", "cd4infgsangue", "cd8il10sangue", "cd8il17sangue", "cd8il4sangue", "cd8il6sangue", "cd8infgsangue", "cd14il10sangueesp", "cd14il12sangueesp", "cd14TGFbsangueesp", "cd14TNFasangueesp", "cd4il10sangueesp", "cd4il17sangueesp", "cd4il4sangueesp", "cd4il6sangueesp", "cd4infgsangueesp", "cd8il10sangueesp", "cd8il17sangueesp", "cd8il4sangueesp", "cd8il6sangueesp", "cd8infgsangueesp", "cd14il10sangueesplei", "cd14il12sangueesplei", "cd14TGFbsangueesplei", "cd14TNFasangueesplei", "cd4il10sangueesplei", "cd4il17sangueesplei", "cd4il4sangueesplei", "cd4il6sangueesplei", "cd4infgsangueesplei", "cd8il10sangueesplei", "cd8il17sangueesplei", "cd8il4sangueesplei", "cd8il6sangueesplei", "cd8infgsangueesplei", "cd14il10sanguelei", "cd14il12sanguelei", "cd14TGFbsanguelei", "cd14TNFasanguelei", "cd4il10sanguelei", "cd4il17sanguelei", "cd4il4sanguelei", "cd4il6sanguelei", "cd4infgsanguelei", "cd8il10sanguelei", "cd8il17sanguelei", "cd8il4sanguelei", "cd8il6sanguelei", "cd8infgsanguelei"), class = "factor")), .Names = c("celula", "tratamento", "sujeito", "ybox", "celtrat"), class = "data.frame", row.names = 225:1120) modnexp1 <- lm(ybox ~ sujeito + celula*tratamento, gnexpo) tabanovn <- Anova(modnexp1,type='III') library(phia) inter <- testInteractions(modnexp1, fixed='celula',across='tratamento') library(multcomp) Tukey <- contrMat(with(gnexpo,tapply(ybox,tratamento,function(x)length(na.omit(x)))), "Tukey")#Acredito que a glht esteja equivocada ao montar os contrastes com dados desbalanceados de acordo com que tem na literatura. Mais ok!!! K1 <- cbind(Tukey, matrix(0, nrow = nrow(Tukey), ncol = ncol(Tukey))) rownames(K1) <- paste(levels(gnexpo$celula)[1], rownames(K1), sep = ":") K2 <- cbind(matrix(0, nrow = nrow(Tukey), ncol = ncol(Tukey)), Tukey) rownames(K2) <- paste(levels(gnexpo$celula)[2], rownames(K2), sep = ":") k1 <- rbind(K1,K2) K <- cbind(matrix(0,nrow(k1),ncol=16), k1, matrix(0,nrow(k1),ncol=47)) colnames(K) <- c(rep('nada',16), rep(colnames(Tukey),2), rep('nada',47)) # Minha dúvida é se de fato a matrix K está montada adequadamente! comp <- lm(ybox ~ sujeito + celtrat-1, gnexpo) rescompe <- glht(comp, linfct=K) rescomp1e <- summary(rescompe) Desde já grato!

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Análise de séries temporais
by Gabriela Alves 15 Dez '15

15 Dez '15

Boa Noite, gostaria te esclarecer uma dúvida que muito impede o avanço do meu projeto, para uns parecerá trivial, mas confesso que para mim está bem complicado.Estou fazendo um estudo do comportamento climático do Estado de São Paulo para os anos considerados normais em comparação aos anos considerados anômalos. Isso me permite gerar uma séria temporal com dados diários de precipitação, umidade e temperatura para os verões de 1961 à 2015. Ao iniciar o processo pelo software R me deparei com a dificuldade falhas serem incorporadas (já que alguns dias, ou meses e até verões completos podem não ter sido aferidos), tendo em vista essa dificuldade fui orientada a utilizar a metodologia de Fourier - ARIMA pois assim seria possível ter uma série completa com dados e falhas para todos os verões previsto. Todavia estou com muita dificuldade em avançar no desenvolvimento dessa série temporal modelagem ARIMA, é algo novo para mim e sendo bem sincera não sei por onde começar. Fazendo buscas descobri que usando o filtro de Kalmam da função auto.arima, é possível a imputação dos dados. Peço gentilmente uma orientação para esclarecer essa minha dúvida. Desde já agradeço. Att. Gabriela Alves

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Dúvida no output da função lme
by Karen Castillioni 14 Dez '15

14 Dez '15

Pessoal, rodei a função lme para testar o efeito de 4 tratamentos (Controle, Corte, H e H+Ct) sobre a cobertura de uma vegetação. Porém ao olhar o output, fiquei em dúvida sobre qual seria o valor de p que devo usar para indicar se houve ou não diferença significativa entre os tratamentos. Alguém sabe qual seria o valor que devo usar? O do "Intercept"? Segue o output: Fixed effects: Cobertura ~ Tratamento Value Std.Error DF t-value p-value (Intercept) 44.79167 3.306008 84 13.548567 0.0000 TratamentoCorte 6.04167 4.675401 8 1.292224 0.2324 TratamentoH -41.91667 4.675401 8 -8.965363 0.0000 TratamentoH+Ct -35.75000 4.675401 8 -7.646403 0.0001 Correlation: (Intr) TrtmnC TrtmnH TratamentoCorte -0.707 TratamentoH -0.707 0.500 TratamentoH+Ct -0.707 0.500 0.500 Obrigada! Karen

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geoR
by Fernanda De Bastiani 14 Dez '15

14 Dez '15

Caros, por favor, alguém poderia me ajudar com a melhor forma de ajusta um modelo sem intercepto no geoR, usando a função likfit? Ou alguma outra função que desempenhe o mesmo papel. Muito obrigada,Fernanda

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