Description Usage Arguments Details Value References Examples
This function is used to add estimated confidence region(s) to an existing probability plot which also includes the estimated regression line.
1 2 3 4 | plot_conf(p_obj, x, y, direction = c("y", "x"),
distribution = c("weibull", "lognormal", "loglogistic", "normal",
"logistic", "sev", "weibull3", "lognormal3", "loglogistic3"),
title_trace = "Confidence Limit")
|
p_obj |
a plotly object provided by function |
x |
a list containing the x-coordinates of the confidence region(s). The list can be of length 1 or 2. For more information see Details. |
y |
a list containing the y-coordinates of the Confidence Region(s). The list can be of length 1 or 2. For more information see Details. |
direction |
a character string specifying the direction of the plotted interval(s). Must be either "y" (failure probabilities) or "x" (quantiles). |
distribution |
supposed distribution of the random variable. The
value can be |
title_trace |
a character string which is assigned to the trace shown in the legend. |
It is important that the length of the vectors provided as lists in x
and y
match with the length of the vectors x
and y
in
the function plot_mod
. For this reason the following procedure
is recommended:
Calculate confidence intervals with the function
confint_betabinom
or confint_fisher
and store
it in a data.frame
. For instance call it df.
Inside plot_mod
use the output df$characteristic
for x
and df$prob
for y
of the function(s) named before.
In Examples the described approach is shown with code.
Returns a plotly object containing the probability plot with plotting positions, the estimated regression line and the estimated confidence region(s).
Meeker, William Q; Escobar, Luis A., Statistical methods for reliability data, New York: Wiley series in probability and statistics, 1998
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 | # Alloy T7987 dataset taken from Meeker and Escobar(1998, p. 131)
cycles <- c(300, 300, 300, 300, 300, 291, 274, 271, 269, 257, 256, 227, 226,
224, 213, 211, 205, 203, 197, 196, 190, 189, 188, 187, 184, 180,
180, 177, 176, 173, 172, 171, 170, 170, 169, 168, 168, 162, 159,
159, 159, 159, 152, 152, 149, 149, 144, 143, 141, 141, 140, 139,
139, 136, 135, 133, 131, 129, 123, 121, 121, 118, 117, 117, 114,
112, 108, 104, 99, 99, 96, 94)
state <- c(rep(0, 5), rep(1, 67))
id <- 1:length(cycles)
df_john <- johnson_method(x = cycles, event = state, id = id)
# Example 1: Probability Plot, Regression Line and Confidence Bounds for Three-Parameter-Weibull:
mrr <- rank_regression(x = df_john$characteristic,
y = df_john$prob,
event = df_john$status,
distribution = "weibull3",
conf_level = .90)
conf_betabin <- confint_betabinom(x = df_john$characteristic,
event = df_john$status,
loc_sc_params = mrr$loc_sc_coefficients,
distribution = "weibull3",
bounds = "two_sided",
conf_level = 0.95,
direction = "y")
plot_weibull <- plot_prob(x = df_john$characteristic,
y = df_john$prob,
event = df_john$status,
id = df_john$id,
distribution = "weibull",
title_main = "Three-Parametric Weibull",
title_x = "Cycles",
title_y = "Probability of Failure in %",
title_trace = "Failed Items")
plot_reg_weibull <- plot_mod(p_obj = plot_weibull,
x = conf_betabin$characteristic,
y = conf_betabin$prob,
loc_sc_params = mrr$loc_sc_coefficients,
distribution = "weibull3",
title_trace = "Estimated Weibull CDF")
plot_conf_beta <- plot_conf(p_obj = plot_reg_weibull,
x = list(conf_betabin$characteristic),
y = list(conf_betabin$lower_bound,
conf_betabin$upper_bound),
direction = "y",
distribution = "weibull3",
title_trace = "Confidence Region")
# Example 2: Probability Plot, Regression Line and Confidence Bounds for Three-Parameter-Lognormal:
mrr_ln <- rank_regression(x = df_john$characteristic,
y = df_john$prob,
event = df_john$status,
distribution = "lognormal3",
conf_level = .90)
conf_betabin_ln <- confint_betabinom(x = df_john$characteristic,
event = df_john$status,
loc_sc_params = mrr_ln$loc_sc_coefficients,
distribution = "lognormal3",
bounds = "two_sided",
conf_level = 0.95,
direction = "y")
plot_lognormal <- plot_prob(x = df_john$characteristic,
y = df_john$prob,
event = df_john$status,
id = df_john$id,
distribution = "lognormal",
title_main = "Three-Parametric Lognormal",
title_x = "Cycles",
title_y = "Probability of Failure in %",
title_trace = "Failed Items")
plot_reg_lognormal <- plot_mod(p_obj = plot_lognormal,
x = conf_betabin_ln$characteristic,
y = conf_betabin_ln$prob,
loc_sc_params = mrr_ln$loc_sc_coefficients,
distribution = "lognormal3",
title_trace = "Estimated Lognormal CDF")
plot_conf_beta_ln <- plot_conf(p_obj = plot_reg_lognormal,
x = list(conf_betabin_ln$characteristic),
y = list(conf_betabin_ln$lower_bound,
conf_betabin_ln$upper_bound),
direction = "y",
distribution = "lognormal3",
title_trace = "Confidence Region")
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