# delivery: Delivery Time Data In robustbase: Basic Robust Statistics

## Description

Delivery Time Data, from Montgomery and Peck (1982). The aim is to explain the time required to service a vending machine (Y) by means of the number of products stocked (X1) and the distance walked by the route driver (X2).

## Usage

 `1` ```data(delivery, package="robustbase") ```

## Format

A data frame with 25 observations on the following 3 variables.

`n.prod`

Number of Products

`distance`

Distance

`delTime`

Delivery time

## Source

Montgomery and Peck (1982, p.116)

## References

P. J. Rousseeuw and A. M. Leroy (1987) Robust Regression and Outlier Detection; Wiley, page 155, table 23.

## Examples

 ```1 2 3 4 5 6``` ```data(delivery) summary(lm.deli <- lm(delTime ~ ., data = delivery)) delivery.x <- as.matrix(delivery[, 1:2]) c_deli <- covMcd(delivery.x) c_deli ```

### Example output

```Call:
lm(formula = delTime ~ ., data = delivery)

Residuals:
Min      1Q  Median      3Q     Max
-5.7880 -0.6629  0.4364  1.1566  7.4197

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.341231   1.096730   2.135 0.044170 *
n.prod      1.615907   0.170735   9.464 3.25e-09 ***
distance    0.014385   0.003613   3.981 0.000631 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 3.259 on 22 degrees of freedom
Multiple R-squared:  0.9596,	Adjusted R-squared:  0.9559
F-statistic: 261.2 on 2 and 22 DF,  p-value: 4.687e-16

Minimum Covariance Determinant (MCD) estimator approximation.
Method: Fast MCD(alpha=0.5 ==> h=14); nsamp = 500; (n,k)mini = (300,5)
Call:
covMcd(x = delivery.x)
Log(Det.):  10.81

Robust Estimate of Location:
n.prod  distance
5.895   268.053
Robust Estimate of Covariance:
n.prod  distance
n.prod     11.66     220.7
distance  220.72   53202.7
```

robustbase documentation built on June 2, 2021, 5:07 p.m.