Plot time series of observed (with lognormally-distributed error bars) vs. predicted data.

## Usage

```
plot_timeseries(
Year,
obs,
fit = NULL,
obs_CV = NULL,
obs_CV_CI = 0.95,
obs_upper = NULL,
obs_lower = NULL,
obs_ind_blue = NULL,
fit_linewidth = 3,
fit_color = "red",
label = "Observed data"
)
```

## Arguments

- Year
A vector of years for the data.

- obs
A vector of observed data.

- fit
A vector of predicted data (e.g., from an assessment model).

- obs_CV
A vector of year-specific coefficient of variation in the observed data.

- obs_CV_CI
The confidence interval for the error bars based for

`obs_CV`

.- obs_upper
A vector of year-specific upper bounds for the error bars of the observed data (in lieu of argument

`obs_CV`

).- obs_lower
A vector of year-specific lower bounds for the error bars of the observed data (in lieu of argument

`obs_CV`

).- obs_ind_blue
Indices of

`obs`

for which the plotted points and error bars will be blue.- fit_linewidth
Argument

`lwd`

for fitted line.- fit_color
Color of fitted line.

- label
Character string that describes the data to label the y-axis.

## Examples

```
data(Red_snapper)
plot_timeseries(Red_snapper@Year, Red_snapper@Cat[1, ],
obs_CV = Red_snapper@CV_Cat, label = "Catch")
```