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ui.R
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ui.R
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library(shiny)
library(shinydashboard)
library(plotly)
setwd("~/Documents/compstat2016/")
dashboardPage(
# Dashboard header
dashboardHeader(title = "Tareas de estadistica Computacional",titleWidth = 250),
dashboardSidebar(
sidebarMenu(
menuItem("Tarea 01", tabName = "tarea_1", icon = icon("unlock")),
menuItem("Tarea 02", tabName = "tarea_2", icon = icon("unlock")),
menuItem("Tarea 04, 05 y 06", tabName = "tarea_4_5_6", icon = icon("unlock"))
)
),
#Body
dashboardBody(
tabItems(
tabItem("tarea_1",
# First Row
fluidRow(
sidebarPanel(
sliderInput("lambda",
"Parámetro lambda",
min = 0,
max = 1,
value = .5),
sliderInput("iterations",
"Número de muestras",
min= 1,
max= 1000,
value= 800),
sliderInput("nbins",
"Números de particiones",
min= 1,
max= 100,
value= 50),
downloadButton('downloadData', 'Descarga muestra')
),
column(6, verbatimTextOutput("chi"))
),
# Second Row
fluidRow(
column(6, plotlyOutput("trendPlot",height = 500)),
column(6, dataTableOutput("tabla"))
)
), # end vis item
# Second menu tab
tabItem("tarea_2",
fluidRow(
sidebarPanel(
numericInput("inf","Limite inferior",value=0),
numericInput("sup","Limite Superior",value = 10),
numericInput("n_sim","Numero de simulaciones",value = 10),
textInput("fun","funcion",value = "function (x) x*3", placeholder = "Funcion a integrar"),
numericInput("confianza", "Intervalo de confianza ", min = 0, max = 1,value = 0.20)
),
column(6, plotOutput("montecarlo_plot_dis",height = 400))
),
fluidRow(
column(6, plotOutput("montecarlo_plot",height = 400)),
column(6, dataTableOutput("tabla_mc"))
)
),
tabItem("tarea_4_5_6",
fluidRow(
sidebarPanel(
titlePanel("Parametros a priori"),
selectInput("dep", "Variable dependiente", c("X" = "dis", "Y" = "pro")),
sliderInput("a", " Parametro a priori a ~ Unif ", min=1, max=10, value=c(1,10)),
sliderInput("b", "Parametro a priori b ~ Unif", min=1, max=10, value=c(1,10)),
sliderInput("sigma", "Parametro a priori sigma ~ Unif", min=1, max=10, value=c(1,10))
),
sidebarPanel(
titlePanel("Parametros MCMC"),
numericInput("n_cadena", "cadenas a simular", value=1, min=1, max=10, step=1),
sliderInput("l_cadena", "longitud de cadenas", min=10000, max=100000, value=10000),
actionButton("run_mcmc_b", "Calcula MCMC")
)
),
fluidRow(
tabsetPanel(type="tabs",
tabPanel("Datos",
fluidRow(
column(6, plotlyOutput("scatter_variables",height = 500)),
column(6, dataTableOutput("tabla_regresion"))
)
),
tabPanel("Cadenas",
fluidRow(
dataTableOutput("cadenasMCMC")
)
),
tabPanel("Histograma a priori",
fluidRow(
column(4, plotlyOutput("histo_a",height = 500)),
column(4, plotlyOutput("histo_b",height = 500)),
column(4, plotlyOutput("histo_sigma",height = 500))
)
),
tabPanel("Histograma posteriori",
fluidRow(
column(4, plotlyOutput("posterior_a",height = 500)),
column(4, plotlyOutput("posterior_b",height = 500)),
column(4, plotlyOutput("posterior_sigma",height = 500))
)
)
)
)
)
) # end tab items
) # end dash body
)