DIconvex {DIconvex} | R Documentation |
Finding patterns of monotonicity and convexity in two-dimensional data
Description
This package takes as input x values x_1,\ldots,x_n
, as well as lower L_1,\ldots,L_n
, and upper bounds U_1,\ldots,U_n
. It maximizes \sum _{i=1}^{n}f_i, \, f_i\in \{0,1\}
such that there exists at least one convex increasing (decreasing) set of values L_j\le y_j\le U_j, j\in C
, where C
is the set of indices i=1,\ldots,n
for which f_i=1
.
Usage
DIconvex(x, lower, upper, increasing = FALSE, epsim = 0, epsic = 0,visual=TRUE)
Arguments
x |
a numeric vector containing a set of points. The elements of |
lower |
a numeric vector of the same length as |
upper |
a numeric vector of the same length as |
increasing |
a boolean value determining whether to look for an increasing or decreasing pattern. The default value is FALSE. |
epsim |
a non-negative value controlling the monotonicity conditions, |
epsic |
a positive value controlling the convexity condition. For |
visual |
a boolean value indicating whether a visual representation of the solution is desired. Here a solution is depicted for all values of x, with linearly interpolated y if |
Details
The package DIconvex
is solved as a linear program facilitating lpSolveAPI
.
It lends itself to applications with financial options data. Given a dataset of call or put options, the function maximizes the number of data points such that there exists at least one set of arbitrage-free fundamental option prices within bid and ask spreads.
For this particular application, x
is the vector of strike prices, lower
represents the vector of bid prices and upper
represents the vector of ask prices.
Value
a list containing:
a vector containing f_1,\ldots,f_n
.
a vector containing y_j, \, j \in C
.
a single integer value containing the status code of the underlying linear program. For the interpretation of status codes please see lpSolveAPI
R documentation. The value 0 signifies success.
Author(s)
Liudmila Karagyaur <liudmila.karagyaur@usi.ch>
Paul Schneider <paul.schneider@usi.ch>
Examples
x = c(315, 320, 325, 330, 335, 340, 345, 350)
upper = c(0.5029714, 0.5633280, 0.6840411, 0.8751702, 3.0000000, 1.5692708, 2.3237279, 3.5207998)
lower = c(0.2514857, 0.4325554, 0.4325554, 0.6236845, 2.5000000, 1.1870125, 1.9414696, 3.1385415)
DIconvex(x, lower, upper, increasing = TRUE)
x = c(340, 345, 350, 355, 360, 365)
lower = c(2.7661994, 1.3177168, 1.5029454, 0.1207069, 0.1207069, 0.1207069)
upper = c(3.1383790, 1.5088361, 1.6236522, 0.3721796, 0.1810603, 0.2514727)
DIconvex(x, lower, upper, increasing = FALSE)