Spaces:
Sleeping
Sleeping
File size: 6,863 Bytes
5227b9c d2f9349 5227b9c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 |
library(shiny)
library(ggplot2)
# Define UI for application that draws a histogram
shinyUI(fluidPage(
# Application title
titlePanel("glm distributions"),
h4("Select the glm distribution and then fixe
the parameters to obtain the probability distribution."),
# Sidebar with a slider input for number of bins
sidebarLayout(
sidebarPanel(
selectInput("Distribucion",
"What distribution?",
choices=c("Normal", "Gamma", "Inv. gaussian",
"Binomial",
"Poisson", "Negative binomial"),
selected="Normal"),
conditionalPanel(condition="input.Distribucion=='Normal'",
numericInput(inputId="mu_normal",
label=HTML("Select μ:"),
value="0.5",
step=0.01),
numericInput(inputId="sigma",
label=HTML("Select σ:"),
min=0.01,
value="1.2",
step=0.01),
numericInput(inputId="min_normal",
label="Select the minimun value for xlim",
value="-1", step=1),
numericInput(inputId="max_normal",
label="Select the maximum value for xlim",
value="3", step=1)
),
conditionalPanel(condition="input.Distribucion=='Gamma'",
numericInput(inputId="mu_gamma",
label=HTML("Select μ:"),
min=0.01,
value=1.5,
step=0.01),
numericInput(inputId="phi_gamma",
label=HTML("Select φ:"),
min=0.01,
value=0.3,
step=0.01),
numericInput(inputId="min_gamma",
label="Select the minimun value for xlim",
value="0.01", step=1),
numericInput(inputId="max_gamma",
label="Select the maximum value for xlim",
value="3", step=1)
),
conditionalPanel(condition="input.Distribucion=='Inv. gaussian'",
numericInput(inputId="mu_invgaus",
label=HTML("Select μ:"),
min=0.01,
value="1.5",
step=0.01),
numericInput(inputId="phi_invgaus",
#label=HTML("Select φ:"),
label="Select φ",
min=0.1,
value="1.2",
step=0.1),
numericInput(inputId="min_invgaus",
label="Select the minimun value for xlim",
value="0.01", step=1),
numericInput(inputId="max_invgaus",
label="Select the maximum value for xlim",
value="3", step=1)
),
conditionalPanel(condition="input.Distribucion=='Binomial'",
numericInput(inputId="mu_binom",
label=HTML("Select μ:"),
min=0.01,
max=0.99,
value=0.3,
step=0.01),
numericInput(inputId="m",
label=HTML("Select m the number of experiments"),
min=1,
value=7,
step=1)
),
conditionalPanel(condition="input.Distribucion=='Poisson'",
numericInput(inputId="mu_pois",
label=HTML("Select μ:"),
min=0.01,
value="2.7",
step=0.01),
numericInput(inputId="max_pois",
label="Select the maximum value for xlim",
value="15", step=1)
),
conditionalPanel(condition="input.Distribucion=='Negative binomial'",
numericInput(inputId="mu_negbin",
label=HTML("Select μ:"),
min=0.01,
value="2.7",
step=0.01),
numericInput(inputId="k",
label=HTML("Select k"),
min=0.01,
value="1.6",
step=0.01),
numericInput(inputId="max_negbin",
label="Select the maximum value for xlim",
value="15", step=1)
),
img(src="logo.png", height = 60, width = 140),
),
# Show a plot of the generated distribution
mainPanel(
plotOutput("distPlot", width = "400px")
)
)
))
|