Illustrating the approach —
x = linspace(0, 5); % Create Data
y = sin(2*pi*x/2.5) + 1.05*x; % Create Data
Rmin = 3.27; % Define Value
ix = find(diff(sign(y-Rmin))); % Find Approximate Index
idxrng = max(1,ix-1) : min(numel(x),ix+1); % Define Index Range
xRmin = interp1(y(idxrng),x(idxrng), Rmin); % X-Coordinate Of Intercept
yRmin = interp1(x(idxrng),y(idxrng), xRmin); % Y-Coordinate Of Intercept
figure
plot(x, y)
hold on
plot([0 xRmin], [1 1]*Rmin, '--r') % Horizontal Dashed Line
plot([1 1]*xRmin, [0 1]*yRmin, '--r') % Vertical Dashed Line
plot(xRmin, yRmin, 'or') % Marker
hold off
grid
text(0,yRmin, 'yR_{min}', 'Horiz','right', 'Vert','middle') % Horizontal Line Axis Label
text(xRmin,0, 'xR_{min}', 'Horiz','center', 'Vert','top') % Vertical Line Axis Label
If you have a vector of the relevant R values, you can put the interp1 calls in a loop and return a vector of the appropriate coordinates. Depending on the initial R values, order the interp1 calls to find the appropriate missing values. The dashed line plot calls can also be in a loop. With respect to 
, there would be two intercepts of the curve for the time values, so you would have to choose the first one (with the lowest index). The others should be striaghtforward.
, there would be two intercepts of the curve for the time values, so you would have to choose the first one (with the lowest index). The others should be striaghtforward. If you are starting with the time values in a vector and have the data for the curve, this is much simpler and only requires a single interp1 call to get all the R values.
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