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ttplot

Plot threshold transitions

Since R2021b

Description

ttplot plots transition functions of threshold transitions. To evaluate the transition function for observations of the threshold variable, use ttdata.

example

ttplot(tt) plots transition bands between states of the threshold transitions tt on the y-axis. The plot shows gradient shading of the mixing level in the transition bands.

example

ttplot(tt,Name,Value) uses additional options specified by one or more name-value arguments. For example, ttplot(tt,Type="graph") specifies plotting a line plot of the transition function at each threshold level on the same axes.

ttplot(ax,___) plots on the axes specified by ax instead of the current axes (gca) using any of the input argument combinations in the previous syntaxes.

h = ttplot(___) returns a handle h to the threshold transitions plot. Use h to modify properties of the plot after you create it.

Examples

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Create discrete threshold transitions at 0 and 2.

t = [0 2];
tt = threshold(t)
tt = 
  threshold with properties:

          Type: 'discrete'
        Levels: [0 2]
         Rates: []
    StateNames: ["1"    "2"    "3"]
     NumStates: 3

tt is a threshold object. The specified thresholds split the space into three states.

Plot the threshold transitions.

ttplot(tt);

ttplot graphs a gradient plot by default. The y-axis represents the value of the threshold variable zt (currently undefined) and the state-space:

  • The system is in state 1 when zt<0.

  • The system is in state 2 when 0zt<2.

  • The system is in state 3 when zt2.

Because the transitions are discrete, ttplot graphs the levels as lines—the regime switches abruptly when zt crosses a threshold variable.

Because zt is undefined, the x-axis is arbitrary. When you specify threshold variable data by using the Data name-value argument, the x-axis is the sample index.

This example shows how to create two logistic threshold transitions with different transition rates, and then display a gradient plot of the transitions.

Load the yearly Canadian inflation and interest rates data set. Extract the inflation rate based on consumer price index (INF_C) from the table, and plot the series.

load Data_Canada
INF_C = DataTable.INF_C;

plot(dates,INF_C);
axis tight

Assume the following characteristics of the inflation rate series:

  • Rates below 2% are low.

  • Rates at least 2% and below 8% are medium.

  • Rates at least 8% are high.

  • A logistic transition function describes the transition between states well.

  • Transition between low and medium rates are faster than transitions between medium and high.

Create threshold transitions to describe the Canadian inflation rates.

t = [2 8];      % Thresholds
r = [3.5 1.5];  % Transition rates
statenames = ["Low" "Med" "High"];
tt = threshold(t,Type="logistic",Rates=r,StateNames=statenames)
tt = 
  threshold with properties:

          Type: 'logistic'
        Levels: [2 8]
         Rates: [3.5000 1.5000]
    StateNames: ["Low"    "Med"    "High"]
     NumStates: 3

Plot the threshold transitions; show the gradient of the transition function between the states, and overlay the data.

figure
ttplot(tt,Data=INF_C)

Create normal cdf threshold transitions at levels 0 and 5, with rates 0.5 and 1.5.

t = [0 5];
r = [0.5 1.5];
tt = threshold(t,Type="normal",Rates=r)
tt = 
  threshold with properties:

          Type: 'normal'
        Levels: [0 5]
         Rates: [0.5000 1.5000]
    StateNames: ["1"    "2"    "3"]
     NumStates: 3

To compare the behavior of the transition functions, plot their graphs at the same level.

figure
ttplot(tt,Type="graph",Width=20)

Plot the transition functions at their levels. Evaluate the transition function over a 1-D grid of values by using ttdata, and then plot the results.

lower = tt.Levels(1) - 3/min(tt.Rates);
upper = tt.Levels(end) + 3/min(tt.Rates);
z = lower:0.1:upper;
F = ttdata(tt,z,UseZeroLevels=false);

figure
plot(z,F,LineWidth=2)
grid on
xlabel("Level")
legend(["Level 0, Rate 0.5" "Level 5, Rate 1.5"],Location="NorthWest")

Create smooth threshold transitions for the Australian to US dollar exchange rate to model price parity.

Load the Australia/US purchasing power and interest rates data set. Extract the log of the exchange rate EXCH from the table.

load Data_JAustralian
EXCH = DataTable.EXCH; 

Consider a two-state system where:

  • State 1 occurs when the Australian dollar buys more than the US dollar (EXCH 0).

  • State 2 occurs when the US dollar buys more than the Australian dollar (EXCH <0).

  • States are weighed more highly as the system deviates from parity (EXCH = 0).

Create threshold transitions representing the system. To attribute a greater amount of mixing away from the threshold, specify an exponential transition function. Set the transition rate to 2.5.

tt = threshold(0,Type="exponential",Rates=2.5)
tt = 
  threshold with properties:

          Type: 'exponential'
        Levels: 0
         Rates: 2.5000
    StateNames: ["1"    "2"]
     NumStates: 2

Plot the threshold transitions with the threshold data.

figure
ttplot(tt,Data=EXCH);

Try improving the display by experimenting with the transition band width (Width name-value argument).

figure
ttplot(tt,Data=EXCH,Width=2);

Plot the transition function.

figure
ttplot(tt,Type="graph");

Input Arguments

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Threshold transitions, with NumStates states, specified as a threshold object. tt must be fully specified (no NaN entries).

Axes on which to plot, specified as an Axes object.

By default, ttplot plots to the current axes (gca).

Name-Value Arguments

Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Example: Type="graph" specifies plotting a line plot of the transition function at each threshold level on the same axes.

Plot type, specified as a value in this table.

ValueDescription
"gradient"Gradient shading of the mixing level in each transition band.
"graph"

Graphs of transition functions at each level.

ttplot plots graphs with levels set to zero.

Example: Type="graph"

Data Types: char | string

Data on a threshold variable zt to include in the plot, specified as a numeric vector.

ttplot plots Data with gradient shading of transition bands (Type="gradient"). If Type="graph", ttplot ignores Data.

Data Types: double

Width of transition bands, specified as a positive numeric scalar.

  • For gradient plots (Type="gradient"), ttplot truncates transition function data outside of the bands.

  • For transition function graphs (Type="graph"), ttplot sets the x-axis limits to [-Width/2 Width/2].

By default, ttplot selects the band width automatically.

Example: Width=10

Data Types: double

Output Arguments

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Plot handle, returned as a graphics object. h contains a unique plot identifier, which you can use to query or modify properties of the plot.

More About

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Mixing Level

The mixing level is the degree to which adjacent states contribute to a response.

Transition functions F vary between 0 and 1; adjacent states are assigned weights F and 1 – F. The mixing level between adjacent states is the minimum weight min(F, 1 – F).

The following characteristics define the mixing behavior of each transition type:

  • Discrete transitions have no mixing.

  • Normal and logistic transitions achieve maximum mixing at threshold levels.

  • Exponential transitions achieve maximum mixing on either side of threshold levels.

For more details, see threshold.

Tips

  • Use the Width name-value argument to adjust the display of transition function graph (Type="graph") plots with varying rates. In multilevel gradient plots (Type="gradient"), a large enough width results in overlapping transition bands that can misrepresent data. By default, ttplot chooses an appropriate width for displaying all transitions.

Version History

Introduced in R2021b