I have data for Hydrogen Sulfide Series, see here http://www.wikiupload.com/Y4WAZJ4Z0IMTK7V I applied a Box-Cox Transformation with $\lambda =1/3$ to try to stabilize the data. I plotted a few sample PACF/ACF to show that the series is not stationary and does not demonstrate constant second order properties with time.
I have eliminated a possible trend and seasonal component by assuming a model of the form $y_t = m_t + s_t + x_t$ where $x_t$ is the stochastic process I am trying to model. I removed a possible seasonal component and a fluctuating mean and I get the following ACF/PACF for my series. Does that look like something that is known? How can I fit a stationary model in R to this? Is it even stationary? Maybe the above decomposition is not really applicable in this case, i.e. the time dependence is more complicated. Here are the resulting ACF-PACF after detrending