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我一直负责采用股票预测模型并将其放入Shiny中。我在R方面的成功一直在上下混合。代码有点混乱，但希望能够通过这一点，并尝试清理它以达到更好的代码。错误：在Shiny应用程序中找不到股票预测模型的功能
我收到错误
Error: could not find function "myATR"
这似乎在那里我建立一个公式字符串给予specifyModel从该行的到来。
这是该行
formula <- as.formula(paste0("Next(Cl(",symbol(),"),",i,") ~ Delt(Cl(",symbol(),"),k=1)+myATR(",symbol(),")+myADX(",symbol(),")+myEMV(",symbol(),")+myVolat(",symbol(),")+myMACD(",symbol(),")+mySAR(",symbol(),")+runMean(Cl(",symbol(),"))"))
公式myATV在代码中定义为
我很为难，不知道如何向别人问这个。我在下面列出了我的ui.R和server.R。
ui.R
# Stock Symbols
# #####
# AAPL - Apple Inc.
# GOOGL - Alphabet Inc.
# ORCL - Oracle Corporation
# FB - Facebook, Inc.
# TWTR - Twitter Inc
shinyUI(fluidPage(
titlePanel("Stock Tickers and Prediction Models, Predicting Future Close Prices"),
sidebarLayout(
sidebarPanel(
selectInput("symbolID", label= "Select ticker",
choices = list("XXII" = 1, "GOOGL" = 2, "ORCL" = 3, "MSFT" = 4, "AIG" = 5)),
selectInput("modelID", label= "Select ticker",
choices = list("svm" = 1, "random forest" = 2, "neural network" = 3))
),
mainPanel(
plotOutput("Graph"),
tableOutput("getsymbols"),
tableOutput("Predictions")
)
)
))
server.R
library(shiny)
library(quantmod)
library(e1071)
library(nlme)
library(earth)
library(xts)
# for stock symbols
symbols = {}
# for model symbols
models = {}
# end date and start dates based on system time
endDate = as.Date(Sys.Date() - 1, format = "%Y-%M-%D")
startDate = as.Date(endDate - 1000, format = "%Y-%M-%D")
myATR <- function(x) ATR(HLC(x))[,'atr']
myADX <- function(x) ADX(HLC(x))[,'ADX']
myEMV <- function(x) EMV(cbind(Hi(x),Lo(x)),Vo(x))[,2]
myMACD <- function(x) MACD(Cl(x))[,2]
mySAR <- function(x) SAR(cbind(Hi(x),Cl(x))) [,1]
myVolat <- function(x) volatility(OHLC(x),calc="garman")[,1]
shinyServer(function(input, output){
inputSymbols <- reactive({
if (input$symbolID == 1) {
symbols = 'XXII'
} else if (input$symbolID == 2) {
symbols = 'GOOGL'
} else if (input$symbolID == 3) {
symbols = 'ORCL'
} else if (input$symbolID == 4) {
symbols = 'MSFT'
} else if (input$symbolID == 5) {
symbols = 'AIG'
}
getSymbols(symbols, src = "yahoo", from = startDate, to = endDate, auto.assign = FALSE)
})
symbol <- reactive({
if (input$symbolID == 1) {
symbols = 'XXII'
} else if (input$symbolID == 2) {
symbols = 'GOOGL'
} else if (input$symbolID == 3) {
symbols = 'ORCL'
} else if (input$symbolID == 4) {
symbols = 'MSFT'
} else if (input$symbolID == 5) {
symbols = 'AIG'
}
symbols
})
model <- reactive({
if (input$modelID == 1) {
models = 1
} else if (input$modelID == 2) {
models = 2
} else if (input$modelID == 3) {
models = 3
}
models
})
#model <- reactive([email protected])
# graph output
output$Graph <- renderPlot({
chartSeries(inputSymbols(), subset = paste(endDate - 30, endDate, sep = "/"), type = 'line', theme = 'white')
})
#output$getsymbols = renderPrint({symbol()})
output$Predictions <- renderTable({
getSymbols(symbol())
#Obtain prediction model for a given iteration
GetPredModel <- function(i){
formula <- as.formula(paste0("Next(Cl(",symbol(),"),",i,") ~ Delt(Cl(",symbol(),"),k=1)+myATR(",symbol(),")+myADX(",symbol(),")+myEMV(",symbol(),")+myVolat(",symbol(),")+myMACD(",symbol(),")+mySAR(",symbol(),")+runMean(Cl(",symbol(),"))"))
#formula <- as.formula(paste0("Next(Cl(",symbol(),")",",",i,") ~ Delt(Cl(",symbol(),"),k=1)+myATR(",symbol(),")+myADX(",symbol(),")+myEMV(",symbol(),")+myVolat(",symbol(),")+myMACD(",symbol(),")+mySAR(",symbol(),")+runMean(Cl(",symbol(),"))"))
m <- specifyModel(formula)
data <- as.data.frame(modelData(m))
return(data)
}
#Derive max data available
maxdate<-max(index(get(symbol())))
#Define prediction as xts object
prediction<-xts()
n=1
while(n<=5){
data<-GetPredModel(n)
formula <- as.formula(paste0("Next.Cl.",symbol(),".",n," ~ ."))
set.seed(1234)
# pick model
if (model() == 1) {
res <- svm(formula,data,cost=10,gamma=0.01)
} else if (model() == 2) {
res<- randomForest(formula,data,na.action = na.omit, ntree=200)
} else if (model() == 3) {
res<-nnet(formula,data, size=10, decay=0.01, maxit=1000, linout=T, trace=F)
}
pred_date<-as.Date(maxdate) + n
p <- predict(res,data[as.character(maxdate),])
#print(pred_date)
names(p)<-c(as.character(pred_date))
prediction<-rbind(as.xts(cbind(p)),prediction)
n = n + 1
}
})
})
这是一个明显的错误，我忽略了！ 我正在处理原始预测文件，然后用Shiny插入，看起来像我没有转移到所有的库。会试试看。 –
看着原来的预测文件，添加以下库： 库（T系列） 库（NNET） 库（quantmod） 库（DMwR） 库（随机森林） 库（TTR） –
加载缺少的库变我与myATR有同样的错误。 –