Predicciones de precios de Indice al Consumidor, utilizando la librería forecast de R

portfolio <- add.constraint(portfolio, type = "full_investment") portfolio <- add.constraint(portfolio, type = "box", min = 0, max = 1) # Add objective to maximize the Sharpe Ratio portfolio <- add.objective(portfolio, type = "risk", name = "StdDev") portfolio <- add.objective(portfolio, type = "return", name = "mean", target = risk_free_rate) portfolio <- add.objective(portfolio, type = "risk_adjusted_return", name = "SharpeRatio", risk_free_rate = risk_free_rate) opt_portfolio_deoptim <- optimize.portfolio(R = returns_xts, portfolio = portfolio, optimize_method = "DEoptim", trace = TRUE)

portfolio <- add.constraint(portfolio, type = "full_investment") portfolio <- add.constraint(portfolio, type = "box", min = 0, max = 1) # Add objective to maximize the Sharpe Ratio portfolio <- add.objective(portfolio, type = "risk", name = "StdDev") portfolio <- add.objective(portfolio, type = "return", name = "mean", target = 0.35/109) portfolio <- add.objective(portfolio, type = "risk_adjusted_return", name = "SharpeRatio", risk_free_rate = risk_free_rate) opt_portfolio_deoptim <- optimize.portfolio(R = returns_xts, portfolio = portfolio, optimize_method = "DEoptim", trace = TRUE)

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Algoritma K-Nearest Neighbors (KNN) dengan R

Class-3, notes of R new group on short-cuts, how to bring the file in R, bar diagram, coloring the Bar

Interactive Scatter Plot scatter_plot <- plot_ly(data = ficus, x = ~Petal_length, y = ~Petal_width, color = ~Species, type = 'scatter', mode = 'markers') %>% layout(title = "Interactive Scatter Plot of Petal Dimensions", xaxis = list(title = "Petal Length"), yaxis = list(title = "Petal Width"), legend = list(orientation = "h", y = -0.3), showlegend = TRUE) scatter_plot

Belanja Kesehatan OOP Rumah Tangga di Jawa Timur 2023

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