{"id":247,"date":"2017-04-18T03:25:03","date_gmt":"2017-04-18T03:25:03","guid":{"rendered":"http:\/\/sites.warnercnr.colostate.edu\/gwhite\/?page_id=247"},"modified":"2017-04-18T03:25:34","modified_gmt":"2017-04-18T03:25:34","slug":"occupancy-estimation-relaxed-closure-assumption","status":"publish","type":"page","link":"https:\/\/sites.warnercnr.colostate.edu\/gwhite\/occupancy-estimation-relaxed-closure-assumption\/","title":{"rendered":"Occupancy Estimation with Relaxed Closure Assumption"},"content":{"rendered":"

Contents<\/a> – Index<\/a><\/span><\/p>\n

\n

Occupancy Estimation with Relaxed Closure Assumption<\/b><\/span><\/p>\n

Single Season<\/b><\/span><\/p>\n

The usual <\/span>single-season occupancy model<\/a><\/span> (data type 27) requires closure over the t<\/i> sampling occasions.\u00a0 That is, the site is either occupied for the entire time, or is not occupied.\u00a0 The model of <\/span>Kendall et al. (2013)<\/a><\/span> allows the site to become occupied and then to become unoccupied later.\u00a0 The model has 4 parameters:<\/span><\/p>\n

psi — probability the site is occupied.\u00a0 Because this is a single-season model, the psi <\/span>PIM<\/a><\/span> has just a single entry.\u00a0\u00a0<\/span><\/p>\n

pent — given that the site is occupied during the season, the probability that the species enters the site between occasions j<\/i> and j<\/i> + 1.\u00a0 This parameter is the beta of the\u00a0 <\/span>Kendall et al. (2013)<\/a><\/span> paper.\u00a0 The <\/span>PIM<\/a><\/span> is a single row with t<\/i> – 1 entries, with the last (t<\/i>th) value obtained by subtraction because the sum of the pent values must be <= 1.\u00a0 Hence, the <\/span>mlogit link<\/a><\/span> is usually used the pent parameter.<\/span><\/p>\n

d<\/i> — given that the species is available for detection at the site on sampling occasion j<\/i>, is the probability that it will depart the site (and therefore unavailable for detection) before sampling occasion j<\/i> + 1.\u00a0 The <\/span>PIM<\/a><\/span> is a single row with t<\/i> – 1 entries, as there are only t<\/i> – 1 parameters.\u00a0<\/span><\/p>\n

p<\/i> — the probability that the species is detected on the site, given that it is available for detection.\u00a0 The <\/span>PIM<\/a><\/span> is a single row with t<\/i> entries for the t<\/i> occasions.<\/span><\/p>\n

This data type is compatible with the <\/span>single-season occupancy model<\/a><\/span>, so that you can run both the usual model and the relaxed closure model in the same <\/span>Results Browser<\/a><\/span>.\u00a0 To jump between these data types, use the <\/span>Change Data Type<\/a><\/span> menu choice under the PIM menu entry.\u00a0 Other single season occupancy models are also available with <\/span>Change Data Type<\/a><\/span>.<\/span>
\n\u00a0\u00a0<\/span>
\nThe addition of parameters to allow entry and departure of the species from the site means that a number of the parameters are not identifiable with a fully time-specific model.\u00a0 One reasonable approach is to fit the time-specific pent parameters with a quadratic function in the <\/span>design matrix<\/a><\/span>.\u00a0 Otherwise, constant d<\/i> or constant p<\/i> models might be considered.<\/span><\/p>\n

Also, this model is a mixture model built on top of another mixture model, so you should be careful to check for multiple optima.\u00a0 The <\/span>Simulated Annealing<\/a><\/span> optimization method should be used routinely to check your results.<\/span><\/p>\n

Four derived parameters are provided: residence time, probability of presence (alpha) for each occasion, and the mean arrival time and the mean departure time.<\/span><\/p>\n

Multiple Seasons<\/b><\/span><\/p>\n

The multiple-season occupancy model (<\/span>Chambert et al. 2015<\/a><\/span>) extends the psi, epsilon, and gamma (data type 30) <\/span>multiple-season occupancy model<\/a><\/span> for each primary occasion as described above for the single season occupancy model with relaxed closure.\u00a0 The pent parameter should normally have the <\/span>mlogit link function<\/a><\/span>.<\/span><\/p>\n

The same 3 derived parameters as the <\/span>multi-season models<\/a><\/span> are included as well as the probability of presence (alpha) for each secondary occasion, mean arrival time for each primary occasion, and mean departure time for each primary occasion.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Contents – Index Occupancy Estimation with Relaxed Closure Assumption Single Season The usual single-season occupancy model (data type 27) requires closure over the t sampling occasions.\u00a0 That is, the site is either occupied for the entire time, or is not …<\/p>\n

Occupancy Estimation with Relaxed Closure Assumption<\/span> Read More »<\/a><\/p>\n","protected":false},"author":117,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-247","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sites.warnercnr.colostate.edu\/gwhite\/wp-json\/wp\/v2\/pages\/247","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.warnercnr.colostate.edu\/gwhite\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.warnercnr.colostate.edu\/gwhite\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.warnercnr.colostate.edu\/gwhite\/wp-json\/wp\/v2\/users\/117"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.warnercnr.colostate.edu\/gwhite\/wp-json\/wp\/v2\/comments?post=247"}],"version-history":[{"count":1,"href":"https:\/\/sites.warnercnr.colostate.edu\/gwhite\/wp-json\/wp\/v2\/pages\/247\/revisions"}],"predecessor-version":[{"id":248,"href":"https:\/\/sites.warnercnr.colostate.edu\/gwhite\/wp-json\/wp\/v2\/pages\/247\/revisions\/248"}],"wp:attachment":[{"href":"https:\/\/sites.warnercnr.colostate.edu\/gwhite\/wp-json\/wp\/v2\/media?parent=247"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}