I'm looking at diversity of bees between different places - inside vs outside apple orchards (Placement), between farms, and between cultivars. All three variables are working fine for honeybees, but for all the solitary ("wildbees") and for some of the bumblebees i get NaNs where I'm supposed to see the results. How can I fix this? Do I simply have too few datapoints? I have just under 500 traps, where I've found ~500 honeybees, ~150 bumblebees and ~70 solitary bees. Sorry if I don't give enough information to answer my question, it's my first time using a forum like this!
Also, what does theta mean? It's not any of my variables
# This is what happened for inside vs outside
> p1 <- zeroinfl(Honeybee...29 ~ Placement, data = diversity, dist = "negbin")
> summary(p1)
Call:
zeroinfl(formula = Honeybee...29 ~ Placement, data = diversity, dist = "negbin")
Pearson residuals:
Min 1Q Median 3Q Max
-0.5872 -0.5872 -0.4080 0.1483 11.2744
Count model coefficients (negbin with log link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.20377 0.11021 1.849 0.0645 .
PlacementWild 0.09042 0.23433 0.386 0.6996
Log(theta) -0.73459 0.16043 -4.579 4.67e-06 ***
Zero-inflation model coefficients (binomial with logit link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) -9.685 53.494 -0.181 0.856
PlacementWild 9.499 53.489 0.178 0.859
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Theta = 0.4797
Number of iterations in BFGS optimization: 127
Log-likelihood: -607.6 on 5 Df
>
> p2 <- zeroinfl(Bumblebee ~ Placement, data = diversity, dist = "negbin")
> summary(p2)
Call:
zeroinfl(formula = Bumblebee ~ Placement, data = diversity, dist = "negbin")
Pearson residuals:
Min 1Q Median 3Q Max
-0.3761 -0.3761 -0.3289 -0.3289 5.9230
Count model coefficients (negbin with log link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) -1.6686 0.1939 -8.607 < 2e-16 ***
PlacementWild 1.8530 0.3853 4.809 1.52e-06 ***
Log(theta) -0.5619 0.5234 -1.074 0.283
Zero-inflation model coefficients (binomial with logit link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) -6.747 76.346 -0.088 0.930
PlacementWild 7.366 76.258 0.097 0.923
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Theta = 0.5701
Number of iterations in BFGS optimization: 84
Log-likelihood: -299.5 on 5 Df
>
> p3 <- zeroinfl(Wildbee ~ Placement, data = diversity, dist = "negbin")
> summary(p3)
Call:
zeroinfl(formula = Wildbee ~ Placement, data = diversity, dist = "negbin")
Pearson residuals:
Min 1Q Median 3Q Max
-0.3369 -0.3369 -0.3132 -0.3132 7.1499
Count model coefficients (negbin with log link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) -1.7629 0.2065 -8.535 < 2e-16 ***
PlacementWild 0.2712 0.2817 0.963 0.336
Log(theta) -1.4738 0.2675 -5.510 3.58e-08 ***
Zero-inflation model coefficients (binomial with logit link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) -12.886 325.692 -0.04 0.968
PlacementWild -7.375 NaN NaN NaN
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Theta = 0.2291
Number of iterations in BFGS optimization: 18
Log-likelihood: -246.7 on 5 Df
Warning message:
In sqrt(diag(object$vcov)) : NaNs produced
This is what happened between farms
> f1 <- zeroinfl(Honeybee...29 ~ Farm, data = diversity, dist = "negbin")
> summary(f1)
Call:
zeroinfl(formula = Honeybee...29 ~ Farm, data = diversity, dist = "negbin")
Pearson residuals:
Min 1Q Median 3Q Max
-0.54910 -0.49323 -0.44511 0.01922 8.19537
Count model coefficients (negbin with log link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.2768 0.1441 1.920 0.0548 .
FarmFruktgården -0.4622 0.3009 -1.536 0.1245
FarmSando -0.1801 0.2744 -0.656 0.5116
Log(theta) -0.9391 0.1857 -5.056 4.27e-07 ***
Zero-inflation model coefficients (binomial with logit link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) -8.688 42.152 -0.206 0.837
FarmFruktgården 7.379 42.133 0.175 0.861
FarmSando 6.753 42.126 0.160 0.873
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Theta = 0.391
Number of iterations in BFGS optimization: 32
Log-likelihood: -612.9 on 7 Df
>
> f2 <- zeroinfl(Bumblebee ~ Farm|Cultivar, data = diversity, dist = "negbin")
> summary(f2)
Call:
zeroinfl(formula = Bumblebee ~ Farm | Cultivar, data = diversity, dist = "negbin")
Pearson residuals:
Min 1Q Median 3Q Max
-0.4019 -0.3099 -0.3099 -0.2951 12.0230
Count model coefficients (negbin with log link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) -1.9397 0.2679 -7.241 4.46e-13 ***
FarmFruktgården 0.1666 0.3705 0.450 0.653
FarmSando 1.4289 0.3324 4.299 1.71e-05 ***
Log(theta) -1.5096 0.2126 -7.102 1.23e-12 ***
Zero-inflation model coefficients (binomial with logit link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) -13.227 362.819 -0.036 0.971
CultivarDiscovery -3.861 NaN NaN NaN
CultivarSummerred -5.736 6888.605 -0.001 0.999
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Theta = 0.221
Number of iterations in BFGS optimization: 14
Log-likelihood: -296.3 on 7 Df
