Frequency table

Description

mytable is used to produce a table of frequencies, proportion and cumulative proportions for a count variable

Usage

myTable(x)

Arguments

Details

myTable is used as either a diagnostic to view the distribution of a count variable, or as a frequency distribution display in its own right. myTable is given in Table 9.40 in Hilbe (2011).

Value

Author(s)

Joseph M. Hilbe, Arizona State University, and Jet Propulsion Laboratory, California Institute of Technology

References

Hilbe, J.M. (2011), Negative Binomial Regression, second edition, Cambridge University Press. Hilbe, J.M. (2009), Logistic Regression Models, Chapman Hall/CRC

See Also

modelfit

Examples

data(medpar)
myTable(medpar$los)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(COUNT)
Loading required package: msme
Loading required package: MASS
Loading required package: lattice
Loading required package: sandwich
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/COUNT/myTable.Rd_%03d_medium.png", width=480, height=480)
> ### Name: myTable
> ### Title: Frequency table
> ### Aliases: myTable
> ### Keywords: table
> 
> ### ** Examples
> 
> data(medpar)
> myTable(medpar$los)
     x Freq         Prop    CumProp
1    1  126 0.0842809365 0.08428094
2    2   71 0.0474916388 0.13177258
3    3   75 0.0501672241 0.18193980
4    4  104 0.0695652174 0.25150502
5    5  123 0.0822742475 0.33377926
6    6   97 0.0648829431 0.39866221
7    7  116 0.0775919732 0.47625418
8    8   92 0.0615384615 0.53779264
9    9   74 0.0494983278 0.58729097
10  10   89 0.0595317726 0.64682274
11  11   70 0.0468227425 0.69364548
12  12   70 0.0468227425 0.74046823
13  13   43 0.0287625418 0.76923077
14  14   49 0.0327759197 0.80200669
15  15   41 0.0274247492 0.82943144
16  16   43 0.0287625418 0.85819398
17  17   29 0.0193979933 0.87759197
18  18   23 0.0153846154 0.89297659
19  19   24 0.0160535117 0.90903010
20  20   19 0.0127090301 0.92173913
21  21   18 0.0120401338 0.93377926
22  22   15 0.0100334448 0.94381271
23  23   10 0.0066889632 0.95050167
24  24   11 0.0073578595 0.95785953
25  25    4 0.0026755853 0.96053512
26  26    7 0.0046822742 0.96521739
27  27    7 0.0046822742 0.96989967
28  28    5 0.0033444816 0.97324415
29  29    3 0.0020066890 0.97525084
30  30    1 0.0006688963 0.97591973
31  31    2 0.0013377926 0.97725753
32  32    6 0.0040133779 0.98127090
33  33    2 0.0013377926 0.98260870
34  34    5 0.0033444816 0.98595318
35  36    1 0.0006688963 0.98662207
36  42    1 0.0006688963 0.98729097
37  43    1 0.0006688963 0.98795987
38  44    2 0.0013377926 0.98929766
39  46    3 0.0020066890 0.99130435
40  48    1 0.0006688963 0.99197324
41  49    1 0.0006688963 0.99264214
42  50    1 0.0006688963 0.99331104
43  52    1 0.0006688963 0.99397993
44  57    1 0.0006688963 0.99464883
45  59    1 0.0006688963 0.99531773
46  60    1 0.0006688963 0.99598662
47  63    1 0.0006688963 0.99665552
48  65    1 0.0006688963 0.99732441
49  70    1 0.0006688963 0.99799331
50  74    1 0.0006688963 0.99866221
51  91    1 0.0006688963 0.99933110
52 116    1 0.0006688963 1.00000000
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>