where Ni is the latent abundance at site i, as with the N-mixture
model, and pij is the multinomial cell probability for transect i
in distance-class j, computed by integrating a detection function
such as the half-normal (with scale parameter s) overeach distance interval (Fiske and Chandler 2011). Abundance
is modeled using a Poisson or negative-binomial distribution.
Four functions (uniform, half-normal, exponential, hazard),
described in further depth by Buckland et al. (2001), were
used to model detection, with distance data formatted in 4-m
bins over the 24 m/side width of the side-scan swath. As
above, sites were assumed to be closed over sampling occasions.
Additional assumptions related to distance sampling
were (1) sturgeon were distributed according to some stochastic
process based on an underlying density, (2) sturgeon were
detected at their initial locations, prior to any movement (to
avoid double-counting), and (3) distances were correctly
grouped by intervals (Buckland et al. 2001). It is generally
assumed for distance surveys that survey lines are randomly
placed, but here, we used a single mid-river survey line. Thus,
we further assumed that sturgeon were randomly distributed
so that our estimated abundances were representative of the
entire surveyed sections of rivers.
ที่ where Ni is the latent abundance at site i, as with the N-mixture
N PIJ model, and pij is the multinomial cell probability for transect i
คือความน่าจะเป็นมือถือพหุนามสำหรับตัดฉันในระยะไกลระดับเจคำนวณโดยการบูรณาการการทำงานของการตรวจสอบดังกล่าวเป็นครึ่งปกติin distance-class j, computed by integrating a detection function
( such as the half-normal (with scale parameter s) overeach distance interval (Fiske and Chandler 2011). Abundance
is modeled using a Poisson or negative-binomial distribution.
Four functions (uniform, half-normal, exponential, hazard),
described in further depth by Buckland et al. (2001), were
used to model detection, with distance data formatted in 4-m
bins over the 24 m/side width of the side-scan swath. As
above, sites were assumed to be closed over sampling occasions.
Additional assumptions related to distance sampling
were (1) sturgeon were distributed according to some stochastic
process based on an underlying density, (2) sturgeon were
detected at their initial locations, prior to any movement (to
avoid double-counting), and (3) distances were correctly
grouped by intervals (Buckland et al. 2001). It is generally
assumed for distance surveys that survey lines are randomly
placed, but here, we used a single mid-river survey line. Thus,
we further assumed that sturgeon were randomly distributed
so that our estimated abundances were representative of the
entire surveyed sections of rivers.
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