inc {assist} | R Documentation |

## Fit a Monotone Curve Using a Cubic Spline

### Description

Return a spline fit of a increasing curve.

### Usage

```
inc(y, x, spar = "v", limnla = c(-6, 0), grid = x, prec = 1e-06, maxit = 50, verbose = F)
```

### Arguments

`y` |
a vecetor, used as the response data |

`x` |
a vector, used as the covariate. Assume an increasing relationshop of |

`spar` |
a character string specifying a method for choosing the smoothing parameter. "v", "m" and "u" represent GCV, GML and UBR respectively. Default is "v" for GCV |

`limnla` |
a vector of length one or two, specifying a search range for log10(n*lambda), where lambda is the smoothing parameter and n is the sample size. If it is a single value, the smoothing parameter will be fixed at this value. |

`grid` |
a vector of |

`prec` |
a numeric value used to assess convergence. Default is 1e-6 |

`maxit` |
an integer represeenting the maximum iterations. Default is 50. |

`verbose` |
an optional logical value. If ‘TRUE’, detailed iteration results are displayed. Default is "FALSE" |

### Details

This function is to fit a increasing fucntion to the data. The monotone function is expressed as integral of an unknown function that a cubic spline is used to estimate.

### Value

a split fit together with the convergence information

### Author(s)

Yuedong Wang yuedong@pstat.ucsb.edu and Chunlei Ke chunlei_ke@yahoo.com

### See Also

`ssr`

*assist*version 3.1.9 Index]