Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.width=6,
fig.height=4
)
## ----setup--------------------------------------------------------------------
library(soiltestcorr)
## ----warning=FALSE, message=FALSE---------------------------------------------
# Install if needed
library(ggplot2) # Plots
library(dplyr) # Data wrangling
library(tidyr) # Data wrangling
library(purrr) # Mapping
## -----------------------------------------------------------------------------
# Native fake dataset from soiltestcorr package
corr_df <- soiltestcorr::data_test
## ----warning=TRUE, message=TRUE-----------------------------------------------
# Type = 1, no restriction (3 parameters)
mitscherlich(corr_df, STV, RY, type = 1)
# Type = 2, fixed asymptote value at 100 (2 parameters)
mitscherlich(corr_df, STV, RY, type = 2)
# Type = 3, fixed origin at 0 and asymptote at 100 (1 parameters)
mitscherlich(corr_df, STV, RY, type = 3)
## ----warning=TRUE, message=TRUE-----------------------------------------------
# Using dataframe argument, tidy = FALSE -> return a LIST
mitscherlich(data = corr_df, STV, RY, target = 90, tidy = FALSE)
## ----warning=TRUE, message=TRUE-----------------------------------------------
fit_vectors_list <-mitscherlich(stv = corr_df$STV,
ry = corr_df$RY,
tidy = FALSE)
fit_vectors_tidy <-mitscherlich(stv = corr_df$STV,
ry = corr_df$RY,
tidy = TRUE)
## ----warning=T, message=F-----------------------------------------------------
# Example 1. Fake dataset manually created
data_1 <- data.frame("RY" = c(65,80,85,88,90,94,93,96,97,95,98,100,99,99,100),
"STV" = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15))
# Example 2. Native fake dataset from soiltestcorr package
data_2 <- soiltestcorr::data_test
# Example 3. Native dataset from soiltestcorr package, Freitas et al. (1966), used by Cate & Nelson (1971)
data_3 <- soiltestcorr::freitas1966 %>%
rename(STV = STK)
data.all <- bind_rows(data_1, data_2, data_3, .id = "id")
## ----warning=T, message=F-----------------------------------------------------
# Run multiple examples at once with map()
data.all %>%
nest(data = c("STV", "RY")) %>%
mutate(model = map(data, ~ mitscherlich(stv = .$STV, ry = .$RY))) %>%
unnest(model)
## ----warning=T, message=F-----------------------------------------------------
data.all %>%
group_by(id) %>%
group_modify(~ soiltestcorr::mitscherlich(data = ., STV, RY))
## -----------------------------------------------------------------------------
set.seed(123)
boot_mits <- boot_mitscherlich(corr_df, STV, RY, target = 90, n = 200)
boot_mits %>% head(n = 5)
# CSTV Confidence Interval
quantile(boot_mits$CSTV, probs = c(0.025, 0.5, 0.975), na.rm = TRUE)
# Plot
boot_mits %>%
ggplot2::ggplot(aes(x = CSTV))+
geom_histogram(color = "grey25", fill = "#9de0bf", bins = 10)
## ----warning=F, message=F-----------------------------------------------------
data_3 <- soiltestcorr::freitas1966
plot_mit <- mitscherlich(data_3, STK, RY, plot = TRUE)
plot_mit
## ----warning=F, message=F-----------------------------------------------------
plot_mit +
# Main title
ggtitle("My own plot title")+
# Axis titles
labs(x = "Soil Test K (ppm)",
y = "Cotton RY(%)") +
# Axis scales
scale_x_continuous(limits = c(20,220),
breaks = seq(0,220, by = 10))
## ----warning=F, message=F-----------------------------------------------------
# Residuals plot
mitscherlich(data_3, STK, RY, resid = TRUE)
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