37 lines
1.4 KiB
R
37 lines
1.4 KiB
R
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rok <- 1995:2002
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liczba_przypadkow <- c(39.7, 38.2, 34.7, 33.1, 30.1, 28.4, 26.3, 24.7)
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data_set <- data.frame(rok = rok, liczba_przypadkow = liczba_przypadkow)
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plot(data_set, main = "Wykres rozrzutu", pch = 16)
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model <- lm(liczba_przypadkow ~ rok, data = data_set)
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model$coefficients
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plot(data_set, main = "Wykres rozrzutu", pch = 16)
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abline(model, col = "red", lwd = 2)
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coef(model)
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confint(model)
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summary(model)
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fitted(model)
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residuals(model)
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temp_rok <- data.frame(rok = seq(min(data_set$rok) - 10,
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max(data_set$rok) + 10,
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length = 100))
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pred <- stats::predict(model, temp_rok, interval = "prediction")
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plot(data_set, main = "Wykres rozrzutu", pch = 16)
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abline(model, col = "red", lwd = 2)
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lines(temp_rok$rok, pred[, 2], lty = 2, col = "red")
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lines(temp_rok$rok, pred[, 3], lty = 2, col = "red")
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new_rok <- data.frame(rok = 2003:2007)
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(pred_2003_2007 <- stats::predict(model, new_rok, interval = 'prediction'))
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plot(data_set, main = "Wykres rozrzutu z predykcją na lata 2003-2007", pch = 16,
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xlim = c(1995, 2007), ylim = c(10, 40))
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abline(model, col = "red", lwd = 2)
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points(2003:2007, pred_2003_2007[, 1], col = "blue", pch = 16)
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temp_rok <- data.frame(rok = seq(1994, 2008, length = 100))
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pred <- stats::predict(model, temp_rok, interval = "prediction")
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lines(temp_rok$rok, pred[, 2], lty = 2, col = "red")
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lines(temp_rok$rok, pred[, 3], lty = 2, col = "red")
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