# Associated S3 methods for nlsBoot from nlstools.

### Description

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.

### Usage

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, ...)
``` |

### Arguments

`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. |

### Details

`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.

### Value

`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.

### Author(s)

Derek H. Ogle, derek@derekogle.com

### See Also

See `summary.nlsBoot`

in nlstools

### Examples

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")
}
``` |