Provides S3 methods to construct non-parametric bootstrap confidence intervals and hypothesis tests for parameter values and predicted values of the response variable for a `nlsBoot`

object from the nlstools package.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
## S3 method for class 'nlsBoot'
confint(object, parm = NULL, level = conf.level,
conf.level = 0.95, plot = FALSE, err.col = "black", err.lwd = 2,
rows = NULL, cols = NULL, ...)
## S3 method for class 'nlsBoot'
predict(object, FUN, conf.level = 0.95, digits = NULL,
...)
htest(object, ...)
## S3 method for class 'nlsBoot'
htest(object, parm = NULL, bo = 0, alt = c("two.sided",
"less", "greater"), plot = FALSE, ...)
``` |

`object` |
An object saved from |

`parm` |
An integer that indicates which parameter to compute the confidence interval or hypothesis test for. The confidence interval Will be computed for all parameters if |

`level` |
Same as |

`conf.level` |
A level of confidence as a proportion. |

`plot` |
A logical that indicates whether a plot should be constructed. If |

`err.col` |
A single numeric or character that identifies the color for the error bars on the plot. |

`err.lwd` |
A single numeric that identifies the line width for the error bars on the plot. |

`rows` |
A numeric that contains the number of rows to use on the graphic. |

`cols` |
A numeric that contains the number of columns to use on the graphic. |

`FUN` |
The function to be applied for the prediction. See the examples. |

`digits` |
A single numeric that indicates the number of digits for the result. |

`bo` |
The null hypothesized parameter value. |

`alt` |
A string that identifies the “direction” of the alternative hypothesis. See details. |

`...` |
Additional arguments to functions. |

`confint`

finds the two quantiles that have the proportion (1-`conf.level`

)/2 of the bootstrapped parameter estimates below and above. This is an approximate 100`conf.level`

% confidence interval.

In `htest`

the “direction” of the alternative hypothesis is identified by a string in the `alt=`

argument. The strings may be `"less"`

for a “less than” alternative, `"greater"`

for a “greater than” alternative, or `"two.sided"`

for a “not equals” alternative (the DEFAULT). In the one-tailed alternatives the p-value is the proportion of bootstrapped parameter estimates in `object$coefboot`

that are extreme of the null hypothesized parameter value in `bo`

. In the two-tailed alternative the p-value is twice the smallest of the proportion of bootstrapped parameter estimates above or below the null hypothesized parameter value in `bo`

.

In `predict`

, a user-supplied function is applied to each row of the `coefBoot`

object in a `nlsBoot`

object and then finds the median and the two quantiles that have the proportion (1-`conf.level`

)/2 of the bootstrapped predictions below and above. The median is returned as the predicted value and the quantiles are returned as an approximate 100`conf.level`

% confidence interval for that prediction.

`confint`

returns a matrix with as many rows as columns (i.e., parameter estimates) in the `object$coefboot`

data frame and two columns of the quantiles that correspond to the approximate confidence interval.

`htest`

returns a matrix with two columns. The first column contains the hypothesized value sent to this function and the second column is the corresponding p-value.

`predict`

returns a matrix with one row and three columns, with the first column holding the predicted value (i.e., the median prediction) and the last two columns holding the approximate confidence interval.

Derek H. Ogle, derek@derekogle.com

See `summary.nlsBoot`

in nlstools

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
data(Ecoli)
fnx <- function(days,B1,B2,B3) {
if (length(B1) > 1) {
B2 <- B1[2]
B3 <- B1[3]
B1 <- B1[1]
}
B1/(1+exp(B2+B3*days))
}
nl1 <- nls(cells~fnx(days,B1,B2,B3),data=Ecoli,start=list(B1=6,B2=7.2,B3=-1.45))
if (require(nlstools)) {
nl1.boot <- nlstools::nlsBoot(nl1,niter=99) # way too few
confint(nl1.boot,"B1")
confint(nl1.boot,c(2,3))
confint(nl1.boot,conf.level=0.90)
predict(nl1.boot,fnx,days=3)
predict(nl1.boot,fnx,days=1:3)
htest(nl1.boot,1,bo=6,alt="less")
}
``` |

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