[R-br] trabalhar com médias

[Edson Lira]

Allan, um CMR é o que nossos amigos precisam para te ajudar.

Poderia postar o teu banco em um site tipo dropbox, datafile host e enviar o link no email para consulta.

De qualquer forma, talvez você possa usar a rotina abaixo:Examples

#AGGREGATE
No R
?aggregate

## Compute the averages for the variables in 'state.x77', grouped
## according to the region (Northeast, South, North Central, West) that
## each state belongs to.
aggregate(state.x77, list(Region = state.region), mean) ## Compute the averages according to region and the occurrence of more
## than 130 days of frost.
aggregate(state.x77, list(Region = state.region, Cold = state.x77[,"Frost"] > 130), mean)
## (Note that no state in 'South' is THAT cold.) ## example with character variables and NAs
testDF <- data.frame(v1 = c(1,3,5,7,8,3,5,NA,4,5,7,9), v2 = c(11,33,55,77,88,33,55,NA,44,55,77,99) )
by1 <- c("red","blue",1,2,NA,"big",1,2,"red",1,NA,12)
by2 <- c("wet","dry",99,95,NA,"damp",95,99,"red",99,NA,NA)
aggregate(x = testDF, by = list(by1, by2), FUN = "mean") # and if you want to treat NAs as a group
fby1 <- factor(by1, exclude = "")
fby2 <- factor(by2, exclude = "")
aggregate(x = testDF, by = list(fby1, fby2), FUN = "mean") ## Formulas, one ~ one, one ~ many, many ~ one, and many ~ many:
aggregate(weight ~ feed, data = chickwts, mean)
aggregate(breaks ~ wool + tension, data = warpbreaks, mean)
aggregate(cbind(Ozone, Temp) ~ Month, data = airquality, mean)
aggregate(cbind(ncases, ncontrols) ~ alcgp + tobgp, data = esoph, sum) ## Dot notation:
aggregate(. ~ Species, data = iris, mean)
aggregate(len ~ ., data = ToothGrowth, mean) ## Often followed by xtabs():
ag <- aggregate(len ~ ., data = ToothGrowth, mean)
xtabs(len ~ ., data = ag) ## Compute the average annual approval ratings for American presidents.
aggregate(presidents, nfrequency = 1, FUN = mean)
## Give the summer less weight.
aggregate(presidents, nfrequency = 1, FUN = weighted.mean, w = c(1, 1, 0.5, 1)) Outra rotina:
No R 
?apply
#APPLY

## Compute row and column sums for a matrix:
x <- cbind(x1 = 3, x2 = c(4:1, 2:5))
dimnames(x)[[1]] <- letters[1:8]
apply(x, 2, mean, trim = .2)
col.sums <- apply(x, 2, sum)
row.sums <- apply(x, 1, sum)
rbind(cbind(x, Rtot = row.sums), Ctot = c(col.sums, sum(col.sums))) stopifnot( apply(x, 2, is.vector)) ## Sort the columns of a matrix
apply(x, 2, sort) ##- function with extra args:
cave <- function(x, c1, c2) c(mean(x[c1]), mean(x[c2]))
apply(x,1, cave,  c1="x1", c2=c("x1","x2")) ma <- matrix(c(1:4, 1, 6:8), nrow = 2)
ma
apply(ma, 1, table)  #--> a list of length 2
apply(ma, 1, stats::quantile)# 5 x n matrix with rownames stopifnot(dim(ma) == dim(apply(ma, 1:2, sum))) ## Example with different lengths for each call
z <- array(1:24, dim=2:4)
zseq <- apply(z, 1:2, function(x) seq_len(max(x)))
zseq         ## a 2 x 3 matrix
typeof(zseq) ## list
dim(zseq) ## 2 3
zseq[1,]
apply(z, 3, function(x) seq_len(max(x)))
# a list without a dim attribute


 
Edson Lira
Estatístico
Manaus-Amazonas


________________________________
 De: "alanarocha em sapo.pt" <alanarocha em sapo.pt>
Para: r-br <r-br em listas.c3sl.ufpr.br> 
Enviadas: Terça-feira, 2 de Julho de 2013 7:41
Assunto: [R-br] trabalhar com médias
 


Olá,
eu tenho estes dados de 4 grupos:
A.       pthi <150    B.       pthi 150-300    C.       pthi 300-600    D. >600
112     277     317     1153
126     208     454     1199
    210     475     2794
    257     444     2081
    246     493     1576
    264     599     901
        589     871
        583     722
        599     1110
        548     1412
        454     732
        382     601
        533     1130
        335     642
        598     682
        448     1035
        355     1203
        462     1136
        500     1109
        354     805
        369     912
        547     1454
            842
            2384
            760
            675
            810
            1215
            1565
            1585
            942
            827
            1015
            631
            647
            709
            2192
            1392
            1028
            1201
            892
            1287
            1579
            1071
            669
            1103
            964
            926
            1501
            979
            1178
            625
            678
            1054
            855
            983
            1076
            876


que codigos eu posso fazer no R para responder a estas perguntas:
7.    Obter a Dose média em cada grupo e o gráfico da sua evolução ao longo do tempo.
Ana

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